1028 Inference Jobs - Page 5

NVIDIA is seeking a dynamic and experienced Generative AI Solution Architect with specialized expertise in training Large Language Models (LLMs) and implementing workflows based on Retrieval-Augmented Generation (RAG). As a key member of our AI Solutions team, you will play a pivotal role in architecting and delivering cutting-edge solutions that leverage the power of NVIDIA's generative AI technologies. This position requires a deep understanding of language models, particularly LLMs, and a strong proficiency in designing and implementing RAG-based workflows. What You Will Be Doing Architect end-to-end generative AI solutions with a focus on LLMs and RAG workflows. Collaborate closely with customers to understand their language-related business challenges and design tailored solutions. Collaborate with sales and business development teams to support pre-sales activities, including technical presentations and demonstrations of LLM and RAG capabilities. Work closely with NVIDIA engineering teams to provide feedback and contribute to the evolution of generative AI technologies. Engage directly with customers to understand their language-related requirements and challenges. Lead workshops and design sessions to define and refine generative AI solutions focused on LLMs and RAG workflows and l ead the training and optimization of Large Language Models using NVIDIA’s hardware and software platforms. Implement strategies for efficient and effective training of LLMs to achieve optimal performance. Design and implement RAG-based workflows to enhance content generation and information retrieval. Work closely with customers to integrate RAG workflows into their applications and systems and s tay abreast of the latest developments in language models and generative AI technologies. Provide technical leadership and guidance on best practices for training LLMs and implementing RAG-based solutions. What We Need To See Master's or Ph.D. in Computer Science, Artificial Intelligence, or equivalent experience 5+ years of hands-on experience in a technical role, specifically focusing on generative AI, with a strong emphasis on training Large Language Models (LLMs). Proven track record of successfully deploying and optimizing LLM models for inference in production environments. In-depth understanding of state-of-the-art language models, including but not limited to GPT-3, BERT, or similar architectures. Expertise in training and fine-tuning LLMs using popular frameworks such as TensorFlow, PyTorch, or Hugging Face Transformers. Proficiency in model deployment and optimization techniques for efficient inference on various hardware platforms, with a focus on GPUs. Strong knowledge of GPU cluster architecture and the ability to leverage parallel processing for accelerated model training and inference. Excellent communication and collaboration skills with the ability to articulate complex technical concepts to both technical and non-technical stakeholders. Experience leading workshops, training sessions, and presenting technical solutions to diverse audiences. Ways to stand out from the crowd Experience in deploying LLM models in cloud environments (e.g., AWS, Azure, GCP) and on-premises infrastructure. Proven ability to optimize LLM models for inference speed, memory efficiency, and resource utilization. Familiarity with containerization technologies (e.g., Docker) and orchestration tools (e.g., Kubernetes) for scalable and efficient model deployment. Deep understanding of GPU cluster architecture, parallel computing, and distributed computing concepts. Hands-on experience with NVIDIA GPU technologies, and GPU cluster management and ability to design and implement scalable and efficient workflows for LLM training and inference on GPU clusters With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you! NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law. JR1995258 Show more Show less

Job Description The ideal candidate must possess in-depth functional knowledge of the process area and apply it to operational scenarios to provide effective solutions. The role enables to identify discrepancies and propose optimal solutions by using a logical, systematic, and sequential methodology. It is vital to be open-minded towards inputs and views from team members and to effectively lead, control, and motivate groups towards company objects. Additionally, candidate must be self-directed, proactive, and seize every opportunity to meet internal and external customer needs and achieve customer satisfaction by effectively auditing processes, implementing best practices and process improvements, and utilizing the frameworks and tools available. Goals and thoughts must be clearly and concisely articulated and conveyed, verbally and in writing, to clients, colleagues, subordinates, and supervisors. Process Manager Role And Responsibilities Set up user journey dashboards across customer touchpoints (web and mobile app) in Adobe analytics, GA4 and Amplitude and identify pain points, familiarity with auditing tags using Omibug, GA debugger and other relevant tools. Understanding and familiarity with cross-device analyses using combined reporting suites, virtual report suite and familiarity with people metric and data warehouse. Building complex segments in analytics tools by going through online user journeys, self-serving tag audit to build segments. Analysis of customer journey and recommend personalization tests on digital properties by using Adobe analytics, GA4, Amplitude or any equivalent tool, walk through of analysis outcome and come up with ideas to optimize digital user experience. Website and mobile app Optimization consulting for client accounts across industries (customer journey analyses and personalization). Familiarity with website measurement strategy, identifying key KPIs and define goals, integrating online and offline data and segmentation strategies. Connect with clients for business requirements, walk through analysis outcome and come up with ideas for optimization of the digital properties. Build analytical reports and dashboards using visualization tools like LookerStudio or PowerBI. Technical And Functional Skills Bachelor’s Degree with overall experience of 6-10 years in digital analytics and optimization (Adobe Analytics, GA4, Appsflyer and Amplitude). Specialism – Adobe Analytics or GA4 and App analytics tools like Amplitude, Appsflyer, Visualization tools Expert- LookerStudio or PowerBI Certification in Adobe Analytics Business practitioner preferred. Ability to drive business inference from quantitative and qualitative datasets. Ability to collaborate with stakeholders across the globe. Strong communication, creative and innovation skills to help develop offerings to meet market needs. About Us At eClerx, we serve some of the largest global companies – 50 of the Fortune 500 clients. Our clients call upon us to solve their most complex problems, and deliver transformative insights. Across roles and levels, you get the opportunity to build expertise, challenge the status quo, think bolder, and help our clients seize value About The Team eClerx is a global leader in productized services, bringing together people, technology and domain expertise to amplify business results. Our mission is to set the benchmark for client service and success in our industry. Our vision is to be the innovation partner of choice for technology, data analytics and process management services. Since our inception in 2000, we've partnered with top companies across various industries, including financial services, telecommunications, retail, and high-tech. Our innovative solutions and domain expertise help businesses optimize operations, improve efficiency, and drive growth. With over 18,000 employees worldwide, eClerx is dedicated to delivering excellence through smart automation and data-driven insights. At eClerx, we believe in nurturing talent and providing hands-on experience. eClerx is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability or protected veteran status, or any other legally protected basis, per applicable law. Show more Show less

Company Description It all started in sunny San Diego, California in 2004 when a visionary engineer, Fred Luddy, saw the potential to transform how we work. Fast forward to today — ServiceNow stands as a global market leader, bringing innovative AI-enhanced technology to over 8,100 customers, including 85% of the Fortune 500®. Our intelligent cloud-based platform seamlessly connects people, systems, and processes to empower organizations to find smarter, faster, and better ways to work. But this is just the beginning of our journey. Join us as we pursue our purpose to make the world work better for everyone. Job Description What you get to do in this role: Generate and evaluate synthetic data tailored to improve the robustness, performance, and safety of machine learning models, particularly large language models (LLMs). Train and fine-tune models using curated datasets, optimizing for performance, reliability, and scalability. Design and implement evaluation metrics to rigorously measure and monitor model quality, safety, and effectiveness. Conduct experiments to validate model behavior and improve generalization across diverse use cases. Collaborate with engineering and research teams to identify risks and recommend AI safety mitigation strategies. Participate in the development, deployment, and continuous improvement of end-to-end AI solutions. Contribute to architectural and technology decisions related to AI infrastructure, frameworks, and tooling. Promote modern engineering practices including continuous integration, continuous delivery, and containerized workflows. Qualifications Key qualifications: 5+ years of experience in machine learning, deep learning, and AI systems. Proficiency in Python and frameworks like PyTorch, TensorFlow, and NumPy. Experience in synthetic data generation, model training, and evaluation in real-world environments. Solid understanding of LLM fine-tuning, prompting, and robustness techniques. Knowledge of AI safety principles and experience identifying and mitigating model risks. Hands-on experience deploying and optimizing models using platforms such as Triton Inference Server. Familiarity with CI/CD, automated testing, and container orchestration tools like Docker and Kubernetes. Additional Information Work Personas We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work. Learn more here. Equal Opportunity Employer ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, creed, religion, sex, sexual orientation, national origin or nationality, ancestry, age, disability, gender identity or expression, marital status, veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements. Accommodations We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact globaltalentss@servicenow.com for assistance. Export Control Regulations For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. From Fortune. ©2024 Fortune Media IP Limited. All rights reserved. Used under license. Show more Show less

Job Title: Computer Vision Engineer Location: Coimbatore, Work from office role Experience Required: 2+ years Employment Type: Full-Time, Permanent Company: Katomaran Technologies About Us Katomaran Technologies is a cutting-edge technology company building real-world AI applications that span across computer vision, large language models (LLMs), and AI agentic systems. We are looking for a highly motivated Senior AI Developer who thrives at the intersection of technology, leadership, and innovation. You will play a core role in architecting AI products, leading engineering teams, and collaborating directly with the founding team and customers to turn vision into scalable, production-ready solutions. Key Responsilbilities Architect and develop scalable AI solutions using computer vision, LLMs, and agent-based AI architectures. Collaborate with the founding team to define product roadmaps and AI strategy. Lead and mentor a team of AI and software engineers, ensuring high code quality and project delivery timelines. Develop robust, efficient pipelines for model training, validation, deployment, and real-time inference. Work closely with customers and internal stakeholders to translate requirements into AI-powered applications. Stay up to date with state-of-the-art research in vision models (YOLO, SAM, CLIP, etc.), transformers, and agentic systems (AutoGPT-style orchestration). Optimize AI models for deployment on cloud and edge environments. Required Skills and Qualifications Bachelor’s or Master’s in Computer Science, AI, Machine Learning, or related fields. 2+ years of hands-on experience building AI applications in computer vision and/or NLP. Strong knowledge of Deep Learning frameworks (PyTorch, TensorFlow, OpenCV, HuggingFace, etc.). Proven experience with LLM fine-tuning, prompt engineering, and embedding-based retrieval (RAG). Solid understanding of agentic systems such as LangGraph, CrewAI, AutoGen, or custom orchestrators. Ability to design and manage production-grade AI systems (Docker, REST APIs, GPU optimization, etc.). Strong communication and leadership skills, with experience managing small to mid-size teams. Startup mindset – self-driven, ownership-oriented, and comfortable in ambiguity. Nice to have Experience with video analytics platforms or edge deployment (Jetson, Coral, etc.). Experience with programming skills in C++ will be an added advantage Knowledge of MLOps practices and tools (MLflow, Weights & Biases, ClearML, etc.). Exposure to Reinforcement Learning or multi-agent collaboration models. Customer-facing experience or involvement in AI product strategy. What we offer Medical insurance Paid sick time Paid time off PF To Apply: Send your resume, GitHub/portfolio, and a brief note about your most exciting AI project to hr@katomaran.com. Show more Show less

Join Tether and Shape the Future of Digital Finance At Tether, we’re not just building products, we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction. Innovate with Tether Tether Finance: Our innovative product suite features the world’s most trusted stablecoin, USDT , relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services. But that’s just the beginning: Tether Power: Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities. Tether Data: Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like KEET , our flagship app that redefines secure and private data sharing. Tether Education : Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity. Tether Evolution : At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways. Why Join Us? Our team is a global talent powerhouse, working remotely from every corner of the world. If you’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We’ve grown fast, stayed lean, and secured our place as a leader in the industry. If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you. Are you ready to be part of the future? About the job As a member of our AI model team, you will drive innovation across the entire AI lifecycle by developing and implementing rigorous evaluation frameworks and benchmark methodologies for pre-training, post-training, and inference. Your work will focus on designing metrics and assessment strategies that ensure our models are highly responsive, efficient, and reliable across real-world applications. You will work on a wide spectrum of systems, from resource-efficient models designed for limited hardware environments to complex, multi-modal architectures that integrate text, images, and audio. We expect you to have deep expertise in advanced model architectures, pre-training and post-training practices, and inference evaluation frameworks. Adopting a hands-on, research-driven approach, you will develop, test, and implement novel evaluation strategies that rigorously track key performance indicators such as accuracy, latency, throughput, and memory footprint. Your evaluations will not only benchmark model performance at each stage, from the foundational pre-training phase to targeted post-training refinements and final inference but will also provide actionable insights. A key element of this role is collaborating with cross-functional teams including product management, engineering, and operations to share your evaluation findings and integrate stakeholder feedback. You will engineer robust evaluation pipelines and performance dashboards that serve as a common reference point for all stakeholders, ensuring that the insights drive continuous improvement in model deployment strategies. The ultimate goal is to set industry-leading standards for AI model quality and reliability, delivering scalable performance and tangible value in dynamic, real-world scenarios. Responsibilities: Develop, test, and deploy integrated frameworks that rigorously assess models during pre-training, post-training, and inference. Define and track key performance indicators such as accuracy, loss metrics, latency, throughput, and memory footprint across diverse deployment scenarios. Curate high-quality evaluation datasets and design standardized benchmarks to reliably measure model quality and robustness. Ensure that these benchmarks accurately reflect improvements achieved through both pre-training and post-training processes, and drive consistency in evaluation practices. Engage with product management, engineering, data science, and operations teams to align evaluation metrics with business objectives. Present evaluation findings, actionable insights, and recommendations through comprehensive dashboards and reports that support decision-making across functions. Systematically analyze evaluation data to identify and resolve bottlenecks across the model lifecycle. Propose and implement optimizations that enhance model performance, scalability, and resource utilization on resource-constrained platforms, ensuring efficient pre-training, post-training, and inference. Conduct iterative experiments and empirical research to refine evaluation methodologies, staying abreast of emerging techniques and trends. Leverage insights to continuously enhance benchmarking practices and improve overall model reliability, ensuring that all stages of the model lifecycle deliver measurable value in real-world applications. A degree in Computer Science or related field. Ideally PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&D (with good publications in A* conferences). Demonstrated experience in designing and evaluating AI models at multiple stages from pre-training, post-training, and inference. You should be proficient in developing evaluation frameworks that rigorously assess accuracy, convergence, loss improvements, and overall model robustness, ensuring each stage of the AI lifecycle delivers measurable real-world value. Strong programming skills and hands-on expertise in evaluation benchmarks and frameworks are essential. Familiarity with building, automating, and scaling complex evaluation and benchmarking pipelines, and experience with performance metrics: latency, throughput, and memory footprint. Proven ability to conduct iterative experiments and empirical research that drive the continuous refinement of evaluation methodologies. You should be adept at staying abreast of emerging trends and techniques, leveraging insights to enhance benchmarking practices and model reliability. Demonstrated experience collaborating with diverse teams such as product, engineering, and operations in order to align evaluation strategies with organizational goals. You must be skilled at translating technical findings into actionable insights for stakeholders and driving process improvements across the model development lifecycle.

We are looking for a talented AI Engineer with 4 + years of experience to join our growing team. In this role, you'll focus on building and refining conversational AI and speech analytics systems , driving innovation in how we process, analyze, and understand voice interactions. Role Objectives: - Design and implement advanced conversational AI solutions - Develop intelligent agent assist features - Optimize real-time natural language understanding and generation - Enhance customer interaction quality through AI technologies Key Responsibilities: - Design and develop machine learning models for intent recognition - Create context-aware dialogue management systems - Implement real-time inference optimization techniques - Build robust natural language understanding pipelines - Develop and maintain speech recognition and synthesis components - Conduct performance testing and model evaluation - Collaborate with product and engineering teams Required Technical Skills: - Advanced proficiency in Python - Deep learning frameworks (TensorFlow/PyTorch/JAX) - Natural Language Processing techniques - Machine learning model development - Real-time system design - Experience with transformer models - Knowledge of dialogue systems architecture - Knowledge of distributed training strategies - Knowledge of model compression techniques Expertise in: - Conversational AI - Machine Learning - Speech recognition - Intent/entity extraction - Context tracking - Dynamic response generation Preferred Background: - Bachelor's or Master's in Computer Science, AI, Computational Linguistics - 4+ years professional experience in conversational AI Preferred Qualifications: - Published research or significant contributions in NLP/AI domains Soft Skills: - Strong problem-solving abilities - Excellent communication skills - Collaborative team player - Innovative thinking - Adaptability in rapidly evolving AI landscape Job Type: Full-time Pay: ₹4,000,000.00 - ₹4,700,000.00 per year Benefits: Flexible schedule Health insurance Leave encashment Paid sick time Paid time off Provident Fund Work from home Schedule: Evening shift Fixed shift Monday to Friday Weekend availability Supplemental Pay: Overtime pay Performance bonus Yearly bonus Work Location: In person

Company Qualcomm India Private Limited Job Area Engineering Group, Engineering Group > Software Engineering General Summary Job Description More Details Below Join the exciting Generative AI team at Qualcomm focused on integrating cutting edge GenAI models on Qualcomm chipsets. The team uses Qualcomm chips’ extensive heterogeneous computing capabilities to allow inference of GenAI models on-device without a need for connection to the cloud. Our inference engine is designed to help developers run neural network models trained in a variety of frameworks on Snapdragon platforms at blazing speeds while still sipping the smallest amount of power. Utilize this power efficient hardware and Software stack to run Large Language Models (LLMs) and Large Vision Models (LVM) at near GPU speeds! Responsibilities In this role, you will spearhead the development and commercialization of the Qualcomm AI Runtime (QAIRT) SDK on Qualcomm SoCs. As an AI inferencing expert, you'll push the limits of performance from large models. Your mastery in deploying large C/C++ software stacks using best practices will be essential. You'll stay on the cutting edge of GenAI advancements, understanding LLMs/Transformers and the nuances of edge-based GenAI deployment. Most importantly, your passion for the role of edge in AI's evolution will be your driving force. Requirements Master’s/Bachelor’s degree in computer science or equivalent. 3+ years of relevant work experience in software development. Strong understanding of Generative AI models – LLM, LVM and LLMs and building blocks Floating-point, Fixed-point representations and Quantization concepts. Experience with optimizing algorithms for AI hardware accelerators (like CPU/GPU/NPU). Strong development skills in C/C++ Excellent analytical and debugging skills. Good communication skills (verbal, presentation, written). Ability to collaborate across a globally diverse team and multiple interests. Preferred Qualifications Strong understanding of SIMD processor architecture and system design. Proficiency in object-oriented software development. Familiarity with Linux and Windows environment Strong background in kernel development for SIMD architectures. Familiarity with frameworks like llama.cpp, MLX, and MLC is a plus. Good knowledge of PyTorch, TFLite, and ONNX Runtime is preferred. Experience with parallel computing systems and Assembly is a plus. Minimum Qualifications Bachelor's degree in Engineering, Information Systems, Computer Science, or related field. Applicants : Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries). Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law. To all Staffing and Recruiting Agencies : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications. If you would like more information about this role, please contact Qualcomm Careers. 3073034 Show more Show less

Description RESPONSIBILITIES Design and implement CI/CD pipelines for AI and ML model training, evaluation, and RAG system deployment (including LLMs, vectorDB, embedding and reranking models, governance and observability systems, and guardrails). Provision and manage AI infrastructure across cloud hyperscalers (AWS/GCP), using infrastructure-as-code tools -strong preference for Terraform-. Maintain containerized environments (Docker, Kubernetes) optimized for GPU workloads and distributed compute. Support vector database, feature store, and embedding store deployments (e.g., pgVector, Pinecone, Redis, Featureform. MongoDB Atlas, etc). Monitor and optimize performance, availability, and cost of AI workloads, using observability tools (e.g., Prometheus, Grafana, Datadog, or managed cloud offerings). Collaborate with data scientists, AI/ML engineers, and other members of the platform team to ensure smooth transitions from experimentation to production. Implement security best practices including secrets management, model access control, data encryption, and audit logging for AI pipelines. Help support the deployment and orchestration of agentic AI systems (LangChain, LangGraph, CrewAI, Copilot Studio, AgentSpace, etc.). Must Haves: 4+ years of DevOps, MLOps, or infrastructure engineering experience. Preferably with 2+ years in AI/ML environments. Hands-on experience with cloud-native services (AWS Bedrock/SageMaker, GCP Vertex AI, or Azure ML) and GPU infrastructure management. Strong skills in CI/CD tools (GitHub Actions, ArgoCD, Jenkins) and configuration management (Ansible, Helm, etc.). Proficient in scripting languages like Python, Bash, -Go or similar is a nice plus-. Experience with monitoring, logging, and alerting systems for AI/ML workloads. Deep understanding of Kubernetes and container lifecycle management. Bonus Attributes: Exposure to MLOps tooling such as MLflow, Kubeflow, SageMaker Pipelines, or Vertex Pipelines. Familiarity with prompt engineering, model fine-tuning, and inference serving. Experience with secure AI deployment and compliance frameworks Knowledge of model versioning, drift detection, and scalable rollback strategies. Abilities: Ability to work with a high level of initiative, accuracy, and attention to detail. Ability to prioritize multiple assignments effectively. Ability to meet established deadlines. Ability to successfully, efficiently, and professionally interact with staff and customers. Excellent organization skills. Critical thinking ability ranging from moderately to highly complex. Flexibility in meeting the business needs of the customer and the company. Ability to work creatively and independently with latitude and minimal supervision. Ability to utilize experience and judgment in accomplishing assigned goals. Experience in navigating organizational structure. Show more Show less

Description RESPONSIBILITIES Design and implement CI/CD pipelines for AI and ML model training, evaluation, and RAG system deployment (including LLMs, vectorDB, embedding and reranking models, governance and observability systems, and guardrails). Provision and manage AI infrastructure across cloud hyperscalers (AWS/GCP), using infrastructure-as-code tools -strong preference for Terraform-. Maintain containerized environments (Docker, Kubernetes) optimized for GPU workloads and distributed compute. Support vector database, feature store, and embedding store deployments (e.g., pgVector, Pinecone, Redis, Featureform. MongoDB Atlas, etc). Monitor and optimize performance, availability, and cost of AI workloads, using observability tools (e.g., Prometheus, Grafana, Datadog, or managed cloud offerings). Collaborate with data scientists, AI/ML engineers, and other members of the platform team to ensure smooth transitions from experimentation to production. Implement security best practices including secrets management, model access control, data encryption, and audit logging for AI pipelines. Help support the deployment and orchestration of agentic AI systems (LangChain, LangGraph, CrewAI, Copilot Studio, AgentSpace, etc.). Must Haves: 4+ years of DevOps, MLOps, or infrastructure engineering experience. Preferably with 2+ years in AI/ML environments. Hands-on experience with cloud-native services (AWS Bedrock/SageMaker, GCP Vertex AI, or Azure ML) and GPU infrastructure management. Strong skills in CI/CD tools (GitHub Actions, ArgoCD, Jenkins) and configuration management (Ansible, Helm, etc.). Proficient in scripting languages like Python, Bash, -Go or similar is a nice plus-. Experience with monitoring, logging, and alerting systems for AI/ML workloads. Deep understanding of Kubernetes and container lifecycle management. Bonus Attributes: Exposure to MLOps tooling such as MLflow, Kubeflow, SageMaker Pipelines, or Vertex Pipelines. Familiarity with prompt engineering, model fine-tuning, and inference serving. Experience with secure AI deployment and compliance frameworks Knowledge of model versioning, drift detection, and scalable rollback strategies. Abilities: Ability to work with a high level of initiative, accuracy, and attention to detail. Ability to prioritize multiple assignments effectively. Ability to meet established deadlines. Ability to successfully, efficiently, and professionally interact with staff and customers. Excellent organization skills. Critical thinking ability ranging from moderately to highly complex. Flexibility in meeting the business needs of the customer and the company. Ability to work creatively and independently with latitude and minimal supervision. Ability to utilize experience and judgment in accomplishing assigned goals. Experience in navigating organizational structure. Show more Show less

Position Title : AI/ML Engineer. Company : Cyfuture India Pvt.Ltd. Industry : IT Services and IT Consulting. Location : Sector 81, NSEZ, Noida (5 Days Work From Office). About Cyfuture Cyfuture is a trusted name in IT services and cloud infrastructure, offering state-of-the-art data center solutions and managed services across platforms like AWS, Azure, and VMWare. We are expanding rapidly in system integration and managed services, building strong alliances with global OEMs like VMWare, AWS, Azure, HP, Dell, Lenovo, and Palo Alto. Position Overview We are hiring an experienced AI/ML Engineer to lead and shape our AI/ML initiatives. The ideal candidate will have hands-on experience in machine learning and artificial intelligence, with strong leadership capabilities and a passion for delivering production-ready solutions. This role involves end-to-end ownership of AI/ML projects, from strategy development to deployment and optimization of large-scale systems. Key Responsibilities Lead and mentor a high-performing AI/ML team. Design and execute AI/ML strategies aligned with business goals. Collaborate with product and engineering teams to identify impactful AI opportunities. Build, train, fine-tune, and deploy ML models in production environments. Manage operations of LLMs and other AI models using modern cloud and MLOps tools. Implement scalable and automated ML pipelines (e., with Kubeflow or MLRun). Handle containerization and orchestration using Docker and Kubernetes. Optimize GPU/TPU resources for training and inference tasks. Develop efficient RAG pipelines with low latency and high retrieval accuracy. Automate CI/CD workflows for continuous integration and delivery of ML systems. Key Skills & Expertise Cloud Computing & Deployment : Proficiency in AWS, Google Cloud, or Azure for scalable model deployment. Familiarity with cloud-native services like AWS SageMaker, Google Vertex AI, or Azure ML. Expertise in Docker and Kubernetes for containerized deployments. Experience with Infrastructure as Code (IaC) using tools like Terraform or CloudFormation. Machine Learning & Deep Learning Strong command of frameworks : TensorFlow, PyTorch, Scikit-learn, XGBoost. Experience with MLOps tools for integration, monitoring, and automation. Expertise in pre-trained models, transfer learning, and designing custom architectures. Programming & Software Engineering Strong skills in Python (NumPy, Pandas, Matplotlib, SciPy) for ML development. Backend/API development with FastAPI, Flask, or Django. Database handling with SQL and NoSQL (PostgreSQL, MongoDB, BigQuery). Familiarity with CI/CD pipelines (GitHub Actions, Jenkins). Scalable AI Systems Proven ability to build AI-driven applications at scale. Handle large datasets, high-throughput requests, and real-time inference. Knowledge of distributed computing : Apache Spark, Dask, Ray. Model Monitoring & Optimization Hands-on with model compression, quantization, and pruning. A/B testing and performance tracking in production. Knowledge of model retraining pipelines for continuous learning. Resource Optimization Efficient use of compute resources : GPUs, TPUs, CPUs. Experience with serverless architectures to reduce cost. Auto-scaling and load balancing for high-traffic systems. Problem-Solving & Collaboration Translate complex ML models into user-friendly applications. Work effectively with data scientists, engineers, and product teams. Write clear technical documentation and architecture reports. (ref:hirist.tech) Show more Show less

Join Tether and Shape the Future of Digital Finance At Tether, we’re not just building products, we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction. Innovate with Tether Tether Finance: Our innovative product suite features the world’s most trusted stablecoin, USDT , relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services. But that’s just the beginning: Tether Power: Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities. Tether Data: Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like KEET , our flagship app that redefines secure and private data sharing. Tether Education : Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity. Tether Evolution : At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways. Why Join Us? Our team is a global talent powerhouse, working remotely from every corner of the world. If you’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We’ve grown fast, stayed lean, and secured our place as a leader in the industry. If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you. Are you ready to be part of the future? About The Job As a member of our AI model team, you will drive innovation in model serving and inference architectures for advanced AI systems. Your work will focus on optimizing model deployment and inference strategies to deliver highly responsive, efficient, and scalable performance across real-world applications. You will work on a wide spectrum of systems, ranging from resource-efficient models designed for limited hardware environments to complex, multi-modal architectures that integrate data such as text, images, and audio. We expect you to have deep expertise in designing and optimizing model serving pipelines and inference frameworks as well as a strong background in advanced model architectures. You will adopt a hands-on, research-driven approach to develop, test, and implement novel serving strategies and inference algorithms. Your responsibilities include engineering robust inference pipelines, establishing comprehensive performance metrics, and identifying and resolving bottlenecks in production environments. The ultimate goal is to enable high-throughput, low-latency, low-memory footprint, and scalable AI performance that delivers tangible value in dynamic, real-world scenarios. Responsibilities: Design and deploy state-of-the-art model serving architectures that deliver high throughput and low latency while optimizing memory usage. Ensure these pipelines run efficiently across diverse environments, including resource-constrained devices and edge platforms. Establish clear performance targets such as reduced latency, improved token response, and minimized memory footprint. Build, run, and monitor controlled inference tests in both simulated and live production environments. Track key performance indicators such as response latency, throughput, memory consumption, and error rates, with special attention to metrics specific to resource-constrained devices. Document iterative results and compare outcomes against established benchmarks to validate performance across platforms. Identify and prepare high-quality test datasets and simulation scenarios tailored to real-world deployment challenges, specifically those encountered on low-resource devices. Set measurable criteria to ensure that these resources effectively evaluate model performance, latency, and memory utilization under various operational conditions. Analyze computational efficiency and diagnose bottlenecks in the serving pipeline by monitoring both processing and memory metrics. Address issues such as suboptimal batch processing, network delays, and high memory usage to optimize the serving infrastructure for scalability and reliability on resource-constrained systems. Work closely with cross-functional teams to integrate optimized serving and inference frameworks into production pipelines designed for edge and on-device applications. Define clear success metrics such as improved real-world performance, low error rates, robust scalability, optimal memory usage and ensure continuous monitoring and iterative refinements for sustained improvements. A degree in Computer Science or related field. Ideally PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&D (with good publications in A* conferences). Proven experience in large-scale model serving and inference optimization is essential. Your contributions should have led to measurable improvements in inference latency, throughput, and memory footprint for domain-specific applications, particularly on resource-constrained devices and edge platforms. A deep understanding of modern model serving architectures and inference optimization techniques is required. This includes state-of-the-art methods for achieving low-latency, high-throughput performance, and efficient memory management in diverse, resource-constrained deployment scenarios. Must have strong expertise in one or more of the following: C/C++, Triton, ThunderKittens, or native CUDA, as well as a deep understanding of model serving frameworks and engines. Practical experience in developing and deploying end-to-end inference pipelines, from optimizing models for efficient serving to integrating these solutions on resource-constrained devices is required. Demonstrated ability to apply empirical research to overcome challenges in model serving, such as latency optimization, computational bottlenecks, and memory constraints. You should be proficient in designing robust evaluation frameworks and iterating on optimization strategies to continuously push the boundaries of inference performance and system efficiency. Show more Show less

At Momenta, we're committed to creating a safer digital world by protecting individuals and businesses from voice-based fraud and scams. Through innovative AI technology and community collaboration, we're building a future where communication is secure and trustworthy. The Role Key Responsibilities Design and Deliver Core Detection Pipeline Lead the development of a robust, modular deepfake detection pipeline capable of ingesting, processing, and classifying real-time audio streams with high accuracy and low latency. Architect the system to operate under telecom-grade conditions with configurable interfaces and scalable deployment strategies. Model Strategy, Development, and Optimization Own the experimentation and refinement of state-of-the-art deep learning models for voice fraud detection. Evaluate multiple model families, benchmark performance across datasets, and strategically select or ensemble models that balance precision, robustness, and compute efficiency for real-world deployment. Latency-Conscious Production Readiness Ensure the entire detection stack meets strict performance targets, including sub-20ms inference latency. Apply industry best practices in model compression, preprocessing optimization, and system-level integration to support high-throughput inference on both CPU and GPU environments. Evaluation Framework and Continuous Testing Design and implement a comprehensive evaluation suite to validate model accuracy, false positive rates, and environmental robustness. Conduct rigorous testing across domains, including cross-corpus validation, telephony channel effects, adversarial scenarios, and environmental noise conditions. Deployment Engineering and API Integration Deliver a fully containerized, production-ready inference service with REST/gRPC endpoints. Build CI/CD pipelines, integration tests, and monitoring hooks to ensure system integrity, traceability, and ease of deployment across environments. Ideal Profile Technical Skills ML Frameworks: PyTorch, TensorFlow, ONNX, OpenVINO, TorchScript Audio Libraries: Librosa, Torchaudio, FFmpeg Model Development: CNNs, Transformers, Wav2Vec/WavLM, AASIST, RawNet Signal Processing: VAD, noise reduction, band-pass filtering, codec simulation Optimization: Quantization, pruning, GPU acceleration DevOps: Git, Docker, CI/CD, FastAPI or Flask, REST/gRPC Preferred Experience Prior work on audio deepfake detection or telephony speech processing Experience with real-time ML model deployment Understanding of adversarial robustness and domain adaptation Familiarity with call center environments or telecom-grade constraints What's on Offer? Excellent career development opportunities Leadership Role Opportunity to make a positive impact Show more Show less

Join us as we work to create a thriving ecosystem that delivers accessible, high-quality, and sustainable healthcare for all. This position requires expertise in designing, developing, debugging, and maintaining AI-powered applications and data engineering workflows for both local and cloud environments. The role involves working on large-scale projects, optimizing AI/ML pipelines, and ensuring scalable data infrastructure. As a PMTS, you will be responsible for integrating Generative AI (GenAI) capabilities, building data pipelines for AI model training, and deploying scalable AI-powered microservices. You will collaborate with AI/ML, Data Engineering, DevOps, and Product teams to deliver impactful solutions that enhance our products and services. Additionally, it would be desirable if the candidate has experience in retrieval-augmented generation (RAG), fine-tuning pre-trained LLMs, AI model evaluation, data pipeline automation, and optimizing cloud-based AI deployments. Responsibilities AI-Powered Software Development & API Integration Develop AI-driven applications, microservices, and automation workflows using FastAPI, Flask, or Django, ensuring cloud-native deployment and performance optimization. Integrate OpenAI APIs (GPT models, Embeddings, Function Calling) and Retrieval-Augmented Generation (RAG) techniques to enhance AI-powered document retrieval, classification, and decision-making. Data Engineering & AI Model Performance Optimization Design, build, and optimize scalable data pipelines for AI/ML workflows using Pandas, PySpark, and Dask, integrating data sources such as Kafka, AWS S3, Azure Data Lake, and Snowflake. Enhance AI model inference efficiency by implementing vector retrieval using FAISS, Pinecone, or ChromaDB, and optimize API latency with tuning techniques (temperature, top-k sampling, max tokens settings). Microservices, APIs & Security Develop scalable RESTful APIs for AI models and data services, ensuring integration with internal and external systems while securing API endpoints using OAuth, JWT, and API Key Authentication. Implement AI-powered logging, observability, and monitoring to track data pipelines, model drift, and inference accuracy, ensuring compliance with AI governance and security best practices. AI & Data Engineering Collaboration Work with AI/ML, Data Engineering, and DevOps teams to optimize AI model deployments, data pipelines, and real-time/batch processing for AI-driven solutions. Engage in Agile ceremonies, backlog refinement, and collaborative problem-solving to scale AI-powered workflows in areas like fraud detection, claims processing, and intelligent automation. Cross-Functional Coordination and Communication Collaborate with Product, UX, and Compliance teams to align AI-powered features with user needs, security policies, and regulatory frameworks (HIPAA, GDPR, SOC2). Ensure seamless integration of structured and unstructured data sources (SQL, NoSQL, vector databases) to improve AI model accuracy and retrieval efficiency. Mentorship & Knowledge Sharing Mentor junior engineers on AI model integration, API development, and scalable data engineering best practices, and conduct knowledge-sharing sessions. Education & Experience Required 12-18 years of experience in software engineering or AI/ML development, preferably in AI-driven solutions. Hands-on experience with Agile development, SDLC, CI/CD pipelines, and AI model deployment lifecycles. Bachelor’s Degree or equivalent in Computer Science, Engineering, Data Science, or a related field. Proficiency in full-stack development with expertise in Python (preferred for AI), Java Experience with structured & unstructured data: SQL (PostgreSQL, MySQL, SQL Server) NoSQL (OpenSearch, Redis, Elasticsearch) Vector Databases (FAISS, Pinecone, ChromaDB) Cloud & AI Infrastructure AWS: Lambda, SageMaker, ECS, S3 Azure: Azure OpenAI, ML Studio GenAI Frameworks & Tools: OpenAI API, Hugging Face Transformers, LangChain, LlamaIndex, AutoGPT, CrewAI. Experience in LLM deployment, retrieval-augmented generation (RAG), and AI search optimization. Proficiency in AI model evaluation (BLEU, ROUGE, BERT Score, cosine similarity) and responsible AI deployment. Strong problem-solving skills, AI ethics awareness, and the ability to collaborate across AI, DevOps, and data engineering teams. Curiosity and eagerness to explore new AI models, tools, and best practices for scalable GenAI adoption. About Athenahealth Here’s our vision: To create a thriving ecosystem that delivers accessible, high-quality, and sustainable healthcare for all. What’s unique about our locations? From an historic, 19th century arsenal to a converted, landmark power plant, all of athenahealth’s offices were carefully chosen to represent our innovative spirit and promote the most positive and productive work environment for our teams. Our 10 offices across the United States and India — plus numerous remote employees — all work to modernize the healthcare experience, together. Our Company Culture Might Be Our Best Feature. We don't take ourselves too seriously. But our work? That’s another story. athenahealth develops and implements products and services that support US healthcare: It’s our chance to create healthier futures for ourselves, for our family and friends, for everyone. Our vibrant and talented employees — or athenistas, as we call ourselves — spark the innovation and passion needed to accomplish our goal. We continue to expand our workforce with amazing people who bring diverse backgrounds, experiences, and perspectives at every level, and foster an environment where every athenista feels comfortable bringing their best selves to work. Our size makes a difference, too: We are small enough that your individual contributions will stand out — but large enough to grow your career with our resources and established business stability. Giving back is integral to our culture. Our athenaGives platform strives to support food security, expand access to high-quality healthcare for all, and support STEM education to develop providers and technologists who will provide access to high-quality healthcare for all in the future. As part of the evolution of athenahealth’s Corporate Social Responsibility (CSR) program, we’ve selected nonprofit partners that align with our purpose and let us foster long-term partnerships for charitable giving, employee volunteerism, insight sharing, collaboration, and cross-team engagement. What can we do for you? Along with health and financial benefits, athenistas enjoy perks specific to each location, including commuter support, employee assistance programs, tuition assistance, employee resource groups, and collaborative workspaces — some offices even welcome dogs. In addition to our traditional benefits and perks, we sponsor events throughout the year, including book clubs, external speakers, and hackathons. And we provide athenistas with a company culture based on learning, the support of an engaged team, and an inclusive environment where all employees are valued. We also encourage a better work-life balance for athenistas with our flexibility. While we know in-office collaboration is critical to our vision, we recognize that not all work needs to be done within an office environment, full-time. With consistent communication and digital collaboration tools, athenahealth enables employees to find a balance that feels fulfilling and productive for each individual situation. Show more Show less

Role : MLOps Engineer Location - Chennai - CKC Mode of Interview - In Person Data - 7th June 2025 (Saturday) Key Words -Skillset AWS SageMaker, Azure ML Studio, GCP Vertex AI PySpark, Azure Databricks MLFlow, KubeFlow, AirFlow, Github Actions, AWS CodePipeline Kubernetes, AKS, Terraform, Fast API Responsibilities Model Deployment, Model Monitoring, Model Retraining Deployment pipeline, Inference pipeline, Monitoring pipeline, Retraining pipeline Drift Detection, Data Drift, Model Drift Experiment Tracking MLOps Architecture REST API publishing Job Responsibilities Research and implement MLOps tools, frameworks and platforms for our Data Science projects. Work on a backlog of activities to raise MLOps maturity in the organization. Proactively introduce a modern, agile and automated approach to Data Science. Conduct internal training and presentations about MLOps tools’ benefits and usage. Required Experience And Qualifications Wide experience with Kubernetes. Experience in operationalization of Data Science projects (MLOps) using at least one of the popular frameworks or platforms (e.g. Kubeflow, AWS Sagemaker, Google AI Platform, Azure Machine Learning, DataRobot, DKube). Good understanding of ML and AI concepts. Hands-on experience in ML model development. Proficiency in Python used both for ML and automation tasks. Good knowledge of Bash and Unix command line toolkit. Experience in CI/CD/CT pipelines implementation. Experience with cloud platforms - preferably AWS - would be an advantage. Show more Show less

Experience : 4.00 + years Salary : INR 4000000-5000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: Customer-Centric Approach, Numpy, opencv, PIL, Pytorch Crop.Photo is Looking for: Our engineers don’t just write code. They frame product logic, shape UX behavior, and ship features. No PMs handing down tickets. No design handoffs. If you think like an owner and love combining deep ML logic with hard product edges — this role is for you. You’ll be working on systems focused on the transformation and generation of millions of visual assets for small-to-large enterprises at scale. What You’ll Do Build and own AI-backed features end to end, from ideation to production — including layout logic, smart cropping, visual enhancement, out-painting and GenAI workflows for background fills Design scalable APIs that wrap vision models like BiRefNet, YOLOv8, Grounding DINO, SAM, CLIP, ControlNet, etc., into batch and real-time pipelines. Write production-grade Python code to manipulate and transform image data using NumPy, OpenCV (cv2), PIL, and PyTorch. Handle pixel-level transformations — from custom masks and color space conversions to geometric warps and contour ops — with speed and precision. Integrate your models into our production web app (AWS based Python/Java backend) and optimize them for latency, memory, and throughput Frame problems when specs are vague — you’ll help define what “good” looks like, and then build it Collaborate with product, UX, and other engineers without relying on formal handoffs — you own your domain What You’ll Need 2–3 years of hands-on experience with vision and image generation models such as YOLO, Grounding DINO, SAM, CLIP, Stable Diffusion, VITON, or TryOnGAN — including experience with inpainting and outpainting workflows using Stable Diffusion pipelines (e.g., Diffusers, InvokeAI, or custom-built solutions) Strong hands-on knowledge of NumPy, OpenCV, PIL, PyTorch, and image visualization/debugging techniques. 1–2 years of experience working with popular LLM APIs such as OpenAI, Anthropic, Gemini and how to compose multi-modal pipelines Solid grasp of production model integration — model loading, GPU/CPU optimization, async inference, caching, and batch processing. Experience solving real-world visual problems like object detection, segmentation, composition, or enhancement. Ability to debug and diagnose visual output errors — e.g., weird segmentation artifacts, off-center crops, broken masks. Deep understanding of image processing in Python: array slicing, color formats, augmentation, geometric transforms, contour detection, etc. Experience building and deploying FastAPI services and containerizing them with Docker for AWS-based infra (ECS, EC2/GPU, Lambda). Solid grasp of production model integration — model loading, GPU/CPU optimization, async inference, caching, and batch processing. A customer-centric approach — you think about how your work affects end users and product experience, not just model performance A quest for high-quality deliverables — you write clean, tested code and debug edge cases until they’re truly fixed The ability to frame problems from scratch and work without strict handoffs — you build from a goal, not a ticket Who You Are You’ve built systems — not just prototypes You care about both ML results and the system’s behavior in production You’re comfortable taking a rough business goal and shaping the technical path to get there You’re energized by product-focused AI work — things that users feel and rely on You’ve worked in or want to work in a startup-grade environment: messy, fast, and impactful How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 4.00 + years Salary : INR 4000000-5000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: Customer-Centric Approach, Numpy, opencv, PIL, Pytorch Crop.Photo is Looking for: Our engineers don’t just write code. They frame product logic, shape UX behavior, and ship features. No PMs handing down tickets. No design handoffs. If you think like an owner and love combining deep ML logic with hard product edges — this role is for you. You’ll be working on systems focused on the transformation and generation of millions of visual assets for small-to-large enterprises at scale. What You’ll Do Build and own AI-backed features end to end, from ideation to production — including layout logic, smart cropping, visual enhancement, out-painting and GenAI workflows for background fills Design scalable APIs that wrap vision models like BiRefNet, YOLOv8, Grounding DINO, SAM, CLIP, ControlNet, etc., into batch and real-time pipelines. Write production-grade Python code to manipulate and transform image data using NumPy, OpenCV (cv2), PIL, and PyTorch. Handle pixel-level transformations — from custom masks and color space conversions to geometric warps and contour ops — with speed and precision. Integrate your models into our production web app (AWS based Python/Java backend) and optimize them for latency, memory, and throughput Frame problems when specs are vague — you’ll help define what “good” looks like, and then build it Collaborate with product, UX, and other engineers without relying on formal handoffs — you own your domain What You’ll Need 2–3 years of hands-on experience with vision and image generation models such as YOLO, Grounding DINO, SAM, CLIP, Stable Diffusion, VITON, or TryOnGAN — including experience with inpainting and outpainting workflows using Stable Diffusion pipelines (e.g., Diffusers, InvokeAI, or custom-built solutions) Strong hands-on knowledge of NumPy, OpenCV, PIL, PyTorch, and image visualization/debugging techniques. 1–2 years of experience working with popular LLM APIs such as OpenAI, Anthropic, Gemini and how to compose multi-modal pipelines Solid grasp of production model integration — model loading, GPU/CPU optimization, async inference, caching, and batch processing. Experience solving real-world visual problems like object detection, segmentation, composition, or enhancement. Ability to debug and diagnose visual output errors — e.g., weird segmentation artifacts, off-center crops, broken masks. Deep understanding of image processing in Python: array slicing, color formats, augmentation, geometric transforms, contour detection, etc. Experience building and deploying FastAPI services and containerizing them with Docker for AWS-based infra (ECS, EC2/GPU, Lambda). Solid grasp of production model integration — model loading, GPU/CPU optimization, async inference, caching, and batch processing. A customer-centric approach — you think about how your work affects end users and product experience, not just model performance A quest for high-quality deliverables — you write clean, tested code and debug edge cases until they’re truly fixed The ability to frame problems from scratch and work without strict handoffs — you build from a goal, not a ticket Who You Are You’ve built systems — not just prototypes You care about both ML results and the system’s behavior in production You’re comfortable taking a rough business goal and shaping the technical path to get there You’re energized by product-focused AI work — things that users feel and rely on You’ve worked in or want to work in a startup-grade environment: messy, fast, and impactful How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 4.00 + years Salary : INR 4000000-5000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: Customer-Centric Approach, Numpy, opencv, PIL, Pytorch Crop.Photo is Looking for: Our engineers don’t just write code. They frame product logic, shape UX behavior, and ship features. No PMs handing down tickets. No design handoffs. If you think like an owner and love combining deep ML logic with hard product edges — this role is for you. You’ll be working on systems focused on the transformation and generation of millions of visual assets for small-to-large enterprises at scale. What You’ll Do Build and own AI-backed features end to end, from ideation to production — including layout logic, smart cropping, visual enhancement, out-painting and GenAI workflows for background fills Design scalable APIs that wrap vision models like BiRefNet, YOLOv8, Grounding DINO, SAM, CLIP, ControlNet, etc., into batch and real-time pipelines. Write production-grade Python code to manipulate and transform image data using NumPy, OpenCV (cv2), PIL, and PyTorch. Handle pixel-level transformations — from custom masks and color space conversions to geometric warps and contour ops — with speed and precision. Integrate your models into our production web app (AWS based Python/Java backend) and optimize them for latency, memory, and throughput Frame problems when specs are vague — you’ll help define what “good” looks like, and then build it Collaborate with product, UX, and other engineers without relying on formal handoffs — you own your domain What You’ll Need 2–3 years of hands-on experience with vision and image generation models such as YOLO, Grounding DINO, SAM, CLIP, Stable Diffusion, VITON, or TryOnGAN — including experience with inpainting and outpainting workflows using Stable Diffusion pipelines (e.g., Diffusers, InvokeAI, or custom-built solutions) Strong hands-on knowledge of NumPy, OpenCV, PIL, PyTorch, and image visualization/debugging techniques. 1–2 years of experience working with popular LLM APIs such as OpenAI, Anthropic, Gemini and how to compose multi-modal pipelines Solid grasp of production model integration — model loading, GPU/CPU optimization, async inference, caching, and batch processing. Experience solving real-world visual problems like object detection, segmentation, composition, or enhancement. Ability to debug and diagnose visual output errors — e.g., weird segmentation artifacts, off-center crops, broken masks. Deep understanding of image processing in Python: array slicing, color formats, augmentation, geometric transforms, contour detection, etc. Experience building and deploying FastAPI services and containerizing them with Docker for AWS-based infra (ECS, EC2/GPU, Lambda). Solid grasp of production model integration — model loading, GPU/CPU optimization, async inference, caching, and batch processing. A customer-centric approach — you think about how your work affects end users and product experience, not just model performance A quest for high-quality deliverables — you write clean, tested code and debug edge cases until they’re truly fixed The ability to frame problems from scratch and work without strict handoffs — you build from a goal, not a ticket Who You Are You’ve built systems — not just prototypes You care about both ML results and the system’s behavior in production You’re comfortable taking a rough business goal and shaping the technical path to get there You’re energized by product-focused AI work — things that users feel and rely on You’ve worked in or want to work in a startup-grade environment: messy, fast, and impactful How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 4.00 + years Salary : INR 4000000-5000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: Customer-Centric Approach, Numpy, opencv, PIL, Pytorch Crop.Photo is Looking for: Our engineers don’t just write code. They frame product logic, shape UX behavior, and ship features. No PMs handing down tickets. No design handoffs. If you think like an owner and love combining deep ML logic with hard product edges — this role is for you. You’ll be working on systems focused on the transformation and generation of millions of visual assets for small-to-large enterprises at scale. What You’ll Do Build and own AI-backed features end to end, from ideation to production — including layout logic, smart cropping, visual enhancement, out-painting and GenAI workflows for background fills Design scalable APIs that wrap vision models like BiRefNet, YOLOv8, Grounding DINO, SAM, CLIP, ControlNet, etc., into batch and real-time pipelines. Write production-grade Python code to manipulate and transform image data using NumPy, OpenCV (cv2), PIL, and PyTorch. Handle pixel-level transformations — from custom masks and color space conversions to geometric warps and contour ops — with speed and precision. Integrate your models into our production web app (AWS based Python/Java backend) and optimize them for latency, memory, and throughput Frame problems when specs are vague — you’ll help define what “good” looks like, and then build it Collaborate with product, UX, and other engineers without relying on formal handoffs — you own your domain What You’ll Need 2–3 years of hands-on experience with vision and image generation models such as YOLO, Grounding DINO, SAM, CLIP, Stable Diffusion, VITON, or TryOnGAN — including experience with inpainting and outpainting workflows using Stable Diffusion pipelines (e.g., Diffusers, InvokeAI, or custom-built solutions) Strong hands-on knowledge of NumPy, OpenCV, PIL, PyTorch, and image visualization/debugging techniques. 1–2 years of experience working with popular LLM APIs such as OpenAI, Anthropic, Gemini and how to compose multi-modal pipelines Solid grasp of production model integration — model loading, GPU/CPU optimization, async inference, caching, and batch processing. Experience solving real-world visual problems like object detection, segmentation, composition, or enhancement. Ability to debug and diagnose visual output errors — e.g., weird segmentation artifacts, off-center crops, broken masks. Deep understanding of image processing in Python: array slicing, color formats, augmentation, geometric transforms, contour detection, etc. Experience building and deploying FastAPI services and containerizing them with Docker for AWS-based infra (ECS, EC2/GPU, Lambda). Solid grasp of production model integration — model loading, GPU/CPU optimization, async inference, caching, and batch processing. A customer-centric approach — you think about how your work affects end users and product experience, not just model performance A quest for high-quality deliverables — you write clean, tested code and debug edge cases until they’re truly fixed The ability to frame problems from scratch and work without strict handoffs — you build from a goal, not a ticket Who You Are You’ve built systems — not just prototypes You care about both ML results and the system’s behavior in production You’re comfortable taking a rough business goal and shaping the technical path to get there You’re energized by product-focused AI work — things that users feel and rely on You’ve worked in or want to work in a startup-grade environment: messy, fast, and impactful How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 4.00 + years Salary : INR 4000000-5000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: Customer-Centric Approach, Numpy, opencv, PIL, Pytorch Crop.Photo is Looking for: Our engineers don’t just write code. They frame product logic, shape UX behavior, and ship features. No PMs handing down tickets. No design handoffs. If you think like an owner and love combining deep ML logic with hard product edges — this role is for you. You’ll be working on systems focused on the transformation and generation of millions of visual assets for small-to-large enterprises at scale. What You’ll Do Build and own AI-backed features end to end, from ideation to production — including layout logic, smart cropping, visual enhancement, out-painting and GenAI workflows for background fills Design scalable APIs that wrap vision models like BiRefNet, YOLOv8, Grounding DINO, SAM, CLIP, ControlNet, etc., into batch and real-time pipelines. Write production-grade Python code to manipulate and transform image data using NumPy, OpenCV (cv2), PIL, and PyTorch. Handle pixel-level transformations — from custom masks and color space conversions to geometric warps and contour ops — with speed and precision. Integrate your models into our production web app (AWS based Python/Java backend) and optimize them for latency, memory, and throughput Frame problems when specs are vague — you’ll help define what “good” looks like, and then build it Collaborate with product, UX, and other engineers without relying on formal handoffs — you own your domain What You’ll Need 2–3 years of hands-on experience with vision and image generation models such as YOLO, Grounding DINO, SAM, CLIP, Stable Diffusion, VITON, or TryOnGAN — including experience with inpainting and outpainting workflows using Stable Diffusion pipelines (e.g., Diffusers, InvokeAI, or custom-built solutions) Strong hands-on knowledge of NumPy, OpenCV, PIL, PyTorch, and image visualization/debugging techniques. 1–2 years of experience working with popular LLM APIs such as OpenAI, Anthropic, Gemini and how to compose multi-modal pipelines Solid grasp of production model integration — model loading, GPU/CPU optimization, async inference, caching, and batch processing. Experience solving real-world visual problems like object detection, segmentation, composition, or enhancement. Ability to debug and diagnose visual output errors — e.g., weird segmentation artifacts, off-center crops, broken masks. Deep understanding of image processing in Python: array slicing, color formats, augmentation, geometric transforms, contour detection, etc. Experience building and deploying FastAPI services and containerizing them with Docker for AWS-based infra (ECS, EC2/GPU, Lambda). Solid grasp of production model integration — model loading, GPU/CPU optimization, async inference, caching, and batch processing. A customer-centric approach — you think about how your work affects end users and product experience, not just model performance A quest for high-quality deliverables — you write clean, tested code and debug edge cases until they’re truly fixed The ability to frame problems from scratch and work without strict handoffs — you build from a goal, not a ticket Who You Are You’ve built systems — not just prototypes You care about both ML results and the system’s behavior in production You’re comfortable taking a rough business goal and shaping the technical path to get there You’re energized by product-focused AI work — things that users feel and rely on You’ve worked in or want to work in a startup-grade environment: messy, fast, and impactful How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 4.00 + years Salary : INR 4000000-5000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: Customer-Centric Approach, Numpy, opencv, PIL, Pytorch Crop.Photo is Looking for: Our engineers don’t just write code. They frame product logic, shape UX behavior, and ship features. No PMs handing down tickets. No design handoffs. If you think like an owner and love combining deep ML logic with hard product edges — this role is for you. You’ll be working on systems focused on the transformation and generation of millions of visual assets for small-to-large enterprises at scale. What You’ll Do Build and own AI-backed features end to end, from ideation to production — including layout logic, smart cropping, visual enhancement, out-painting and GenAI workflows for background fills Design scalable APIs that wrap vision models like BiRefNet, YOLOv8, Grounding DINO, SAM, CLIP, ControlNet, etc., into batch and real-time pipelines. Write production-grade Python code to manipulate and transform image data using NumPy, OpenCV (cv2), PIL, and PyTorch. Handle pixel-level transformations — from custom masks and color space conversions to geometric warps and contour ops — with speed and precision. Integrate your models into our production web app (AWS based Python/Java backend) and optimize them for latency, memory, and throughput Frame problems when specs are vague — you’ll help define what “good” looks like, and then build it Collaborate with product, UX, and other engineers without relying on formal handoffs — you own your domain What You’ll Need 2–3 years of hands-on experience with vision and image generation models such as YOLO, Grounding DINO, SAM, CLIP, Stable Diffusion, VITON, or TryOnGAN — including experience with inpainting and outpainting workflows using Stable Diffusion pipelines (e.g., Diffusers, InvokeAI, or custom-built solutions) Strong hands-on knowledge of NumPy, OpenCV, PIL, PyTorch, and image visualization/debugging techniques. 1–2 years of experience working with popular LLM APIs such as OpenAI, Anthropic, Gemini and how to compose multi-modal pipelines Solid grasp of production model integration — model loading, GPU/CPU optimization, async inference, caching, and batch processing. Experience solving real-world visual problems like object detection, segmentation, composition, or enhancement. Ability to debug and diagnose visual output errors — e.g., weird segmentation artifacts, off-center crops, broken masks. Deep understanding of image processing in Python: array slicing, color formats, augmentation, geometric transforms, contour detection, etc. Experience building and deploying FastAPI services and containerizing them with Docker for AWS-based infra (ECS, EC2/GPU, Lambda). Solid grasp of production model integration — model loading, GPU/CPU optimization, async inference, caching, and batch processing. A customer-centric approach — you think about how your work affects end users and product experience, not just model performance A quest for high-quality deliverables — you write clean, tested code and debug edge cases until they’re truly fixed The ability to frame problems from scratch and work without strict handoffs — you build from a goal, not a ticket Who You Are You’ve built systems — not just prototypes You care about both ML results and the system’s behavior in production You’re comfortable taking a rough business goal and shaping the technical path to get there You’re energized by product-focused AI work — things that users feel and rely on You’ve worked in or want to work in a startup-grade environment: messy, fast, and impactful How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 4.00 + years Salary : INR 4000000-5000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: Customer-Centric Approach, Numpy, opencv, PIL, Pytorch Crop.Photo is Looking for: Our engineers don’t just write code. They frame product logic, shape UX behavior, and ship features. No PMs handing down tickets. No design handoffs. If you think like an owner and love combining deep ML logic with hard product edges — this role is for you. You’ll be working on systems focused on the transformation and generation of millions of visual assets for small-to-large enterprises at scale. What You’ll Do Build and own AI-backed features end to end, from ideation to production — including layout logic, smart cropping, visual enhancement, out-painting and GenAI workflows for background fills Design scalable APIs that wrap vision models like BiRefNet, YOLOv8, Grounding DINO, SAM, CLIP, ControlNet, etc., into batch and real-time pipelines. Write production-grade Python code to manipulate and transform image data using NumPy, OpenCV (cv2), PIL, and PyTorch. Handle pixel-level transformations — from custom masks and color space conversions to geometric warps and contour ops — with speed and precision. Integrate your models into our production web app (AWS based Python/Java backend) and optimize them for latency, memory, and throughput Frame problems when specs are vague — you’ll help define what “good” looks like, and then build it Collaborate with product, UX, and other engineers without relying on formal handoffs — you own your domain What You’ll Need 2–3 years of hands-on experience with vision and image generation models such as YOLO, Grounding DINO, SAM, CLIP, Stable Diffusion, VITON, or TryOnGAN — including experience with inpainting and outpainting workflows using Stable Diffusion pipelines (e.g., Diffusers, InvokeAI, or custom-built solutions) Strong hands-on knowledge of NumPy, OpenCV, PIL, PyTorch, and image visualization/debugging techniques. 1–2 years of experience working with popular LLM APIs such as OpenAI, Anthropic, Gemini and how to compose multi-modal pipelines Solid grasp of production model integration — model loading, GPU/CPU optimization, async inference, caching, and batch processing. Experience solving real-world visual problems like object detection, segmentation, composition, or enhancement. Ability to debug and diagnose visual output errors — e.g., weird segmentation artifacts, off-center crops, broken masks. Deep understanding of image processing in Python: array slicing, color formats, augmentation, geometric transforms, contour detection, etc. Experience building and deploying FastAPI services and containerizing them with Docker for AWS-based infra (ECS, EC2/GPU, Lambda). Solid grasp of production model integration — model loading, GPU/CPU optimization, async inference, caching, and batch processing. A customer-centric approach — you think about how your work affects end users and product experience, not just model performance A quest for high-quality deliverables — you write clean, tested code and debug edge cases until they’re truly fixed The ability to frame problems from scratch and work without strict handoffs — you build from a goal, not a ticket Who You Are You’ve built systems — not just prototypes You care about both ML results and the system’s behavior in production You’re comfortable taking a rough business goal and shaping the technical path to get there You’re energized by product-focused AI work — things that users feel and rely on You’ve worked in or want to work in a startup-grade environment: messy, fast, and impactful How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 4.00 + years Salary : INR 4000000-5000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: Customer-Centric Approach, Numpy, opencv, PIL, Pytorch Crop.Photo is Looking for: Our engineers don’t just write code. They frame product logic, shape UX behavior, and ship features. No PMs handing down tickets. No design handoffs. If you think like an owner and love combining deep ML logic with hard product edges — this role is for you. You’ll be working on systems focused on the transformation and generation of millions of visual assets for small-to-large enterprises at scale. What You’ll Do Build and own AI-backed features end to end, from ideation to production — including layout logic, smart cropping, visual enhancement, out-painting and GenAI workflows for background fills Design scalable APIs that wrap vision models like BiRefNet, YOLOv8, Grounding DINO, SAM, CLIP, ControlNet, etc., into batch and real-time pipelines. Write production-grade Python code to manipulate and transform image data using NumPy, OpenCV (cv2), PIL, and PyTorch. Handle pixel-level transformations — from custom masks and color space conversions to geometric warps and contour ops — with speed and precision. Integrate your models into our production web app (AWS based Python/Java backend) and optimize them for latency, memory, and throughput Frame problems when specs are vague — you’ll help define what “good” looks like, and then build it Collaborate with product, UX, and other engineers without relying on formal handoffs — you own your domain What You’ll Need 2–3 years of hands-on experience with vision and image generation models such as YOLO, Grounding DINO, SAM, CLIP, Stable Diffusion, VITON, or TryOnGAN — including experience with inpainting and outpainting workflows using Stable Diffusion pipelines (e.g., Diffusers, InvokeAI, or custom-built solutions) Strong hands-on knowledge of NumPy, OpenCV, PIL, PyTorch, and image visualization/debugging techniques. 1–2 years of experience working with popular LLM APIs such as OpenAI, Anthropic, Gemini and how to compose multi-modal pipelines Solid grasp of production model integration — model loading, GPU/CPU optimization, async inference, caching, and batch processing. Experience solving real-world visual problems like object detection, segmentation, composition, or enhancement. Ability to debug and diagnose visual output errors — e.g., weird segmentation artifacts, off-center crops, broken masks. Deep understanding of image processing in Python: array slicing, color formats, augmentation, geometric transforms, contour detection, etc. Experience building and deploying FastAPI services and containerizing them with Docker for AWS-based infra (ECS, EC2/GPU, Lambda). Solid grasp of production model integration — model loading, GPU/CPU optimization, async inference, caching, and batch processing. A customer-centric approach — you think about how your work affects end users and product experience, not just model performance A quest for high-quality deliverables — you write clean, tested code and debug edge cases until they’re truly fixed The ability to frame problems from scratch and work without strict handoffs — you build from a goal, not a ticket Who You Are You’ve built systems — not just prototypes You care about both ML results and the system’s behavior in production You’re comfortable taking a rough business goal and shaping the technical path to get there You’re energized by product-focused AI work — things that users feel and rely on You’ve worked in or want to work in a startup-grade environment: messy, fast, and impactful How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 4.00 + years Salary : INR 4000000-5000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: Customer-Centric Approach, Numpy, opencv, PIL, Pytorch Crop.Photo is Looking for: Our engineers don’t just write code. They frame product logic, shape UX behavior, and ship features. No PMs handing down tickets. No design handoffs. If you think like an owner and love combining deep ML logic with hard product edges — this role is for you. You’ll be working on systems focused on the transformation and generation of millions of visual assets for small-to-large enterprises at scale. What You’ll Do Build and own AI-backed features end to end, from ideation to production — including layout logic, smart cropping, visual enhancement, out-painting and GenAI workflows for background fills Design scalable APIs that wrap vision models like BiRefNet, YOLOv8, Grounding DINO, SAM, CLIP, ControlNet, etc., into batch and real-time pipelines. Write production-grade Python code to manipulate and transform image data using NumPy, OpenCV (cv2), PIL, and PyTorch. Handle pixel-level transformations — from custom masks and color space conversions to geometric warps and contour ops — with speed and precision. Integrate your models into our production web app (AWS based Python/Java backend) and optimize them for latency, memory, and throughput Frame problems when specs are vague — you’ll help define what “good” looks like, and then build it Collaborate with product, UX, and other engineers without relying on formal handoffs — you own your domain What You’ll Need 2–3 years of hands-on experience with vision and image generation models such as YOLO, Grounding DINO, SAM, CLIP, Stable Diffusion, VITON, or TryOnGAN — including experience with inpainting and outpainting workflows using Stable Diffusion pipelines (e.g., Diffusers, InvokeAI, or custom-built solutions) Strong hands-on knowledge of NumPy, OpenCV, PIL, PyTorch, and image visualization/debugging techniques. 1–2 years of experience working with popular LLM APIs such as OpenAI, Anthropic, Gemini and how to compose multi-modal pipelines Solid grasp of production model integration — model loading, GPU/CPU optimization, async inference, caching, and batch processing. Experience solving real-world visual problems like object detection, segmentation, composition, or enhancement. Ability to debug and diagnose visual output errors — e.g., weird segmentation artifacts, off-center crops, broken masks. Deep understanding of image processing in Python: array slicing, color formats, augmentation, geometric transforms, contour detection, etc. Experience building and deploying FastAPI services and containerizing them with Docker for AWS-based infra (ECS, EC2/GPU, Lambda). Solid grasp of production model integration — model loading, GPU/CPU optimization, async inference, caching, and batch processing. A customer-centric approach — you think about how your work affects end users and product experience, not just model performance A quest for high-quality deliverables — you write clean, tested code and debug edge cases until they’re truly fixed The ability to frame problems from scratch and work without strict handoffs — you build from a goal, not a ticket Who You Are You’ve built systems — not just prototypes You care about both ML results and the system’s behavior in production You’re comfortable taking a rough business goal and shaping the technical path to get there You’re energized by product-focused AI work — things that users feel and rely on You’ve worked in or want to work in a startup-grade environment: messy, fast, and impactful How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 4.00 + years Salary : INR 4000000-5000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: Customer-Centric Approach, Numpy, opencv, PIL, Pytorch Crop.Photo is Looking for: Our engineers don’t just write code. They frame product logic, shape UX behavior, and ship features. No PMs handing down tickets. No design handoffs. If you think like an owner and love combining deep ML logic with hard product edges — this role is for you. You’ll be working on systems focused on the transformation and generation of millions of visual assets for small-to-large enterprises at scale. What You’ll Do Build and own AI-backed features end to end, from ideation to production — including layout logic, smart cropping, visual enhancement, out-painting and GenAI workflows for background fills Design scalable APIs that wrap vision models like BiRefNet, YOLOv8, Grounding DINO, SAM, CLIP, ControlNet, etc., into batch and real-time pipelines. Write production-grade Python code to manipulate and transform image data using NumPy, OpenCV (cv2), PIL, and PyTorch. Handle pixel-level transformations — from custom masks and color space conversions to geometric warps and contour ops — with speed and precision. Integrate your models into our production web app (AWS based Python/Java backend) and optimize them for latency, memory, and throughput Frame problems when specs are vague — you’ll help define what “good” looks like, and then build it Collaborate with product, UX, and other engineers without relying on formal handoffs — you own your domain What You’ll Need 2–3 years of hands-on experience with vision and image generation models such as YOLO, Grounding DINO, SAM, CLIP, Stable Diffusion, VITON, or TryOnGAN — including experience with inpainting and outpainting workflows using Stable Diffusion pipelines (e.g., Diffusers, InvokeAI, or custom-built solutions) Strong hands-on knowledge of NumPy, OpenCV, PIL, PyTorch, and image visualization/debugging techniques. 1–2 years of experience working with popular LLM APIs such as OpenAI, Anthropic, Gemini and how to compose multi-modal pipelines Solid grasp of production model integration — model loading, GPU/CPU optimization, async inference, caching, and batch processing. Experience solving real-world visual problems like object detection, segmentation, composition, or enhancement. Ability to debug and diagnose visual output errors — e.g., weird segmentation artifacts, off-center crops, broken masks. Deep understanding of image processing in Python: array slicing, color formats, augmentation, geometric transforms, contour detection, etc. Experience building and deploying FastAPI services and containerizing them with Docker for AWS-based infra (ECS, EC2/GPU, Lambda). Solid grasp of production model integration — model loading, GPU/CPU optimization, async inference, caching, and batch processing. A customer-centric approach — you think about how your work affects end users and product experience, not just model performance A quest for high-quality deliverables — you write clean, tested code and debug edge cases until they’re truly fixed The ability to frame problems from scratch and work without strict handoffs — you build from a goal, not a ticket Who You Are You’ve built systems — not just prototypes You care about both ML results and the system’s behavior in production You’re comfortable taking a rough business goal and shaping the technical path to get there You’re energized by product-focused AI work — things that users feel and rely on You’ve worked in or want to work in a startup-grade environment: messy, fast, and impactful How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less

Experience : 4.00 + years Salary : INR 4000000-5000000 / year (based on experience) Expected Notice Period : 15 Days Shift : (GMT+05:30) Asia/Kolkata (IST) Opportunity Type : Remote Placement Type : Full Time Permanent position(Payroll and Compliance to be managed by: Crop.Photo) (*Note: This is a requirement for one of Uplers' client - Crop.Photo) What do you need for this opportunity? Must have skills required: Customer-Centric Approach, Numpy, opencv, PIL, Pytorch Crop.Photo is Looking for: Our engineers don’t just write code. They frame product logic, shape UX behavior, and ship features. No PMs handing down tickets. No design handoffs. If you think like an owner and love combining deep ML logic with hard product edges — this role is for you. You’ll be working on systems focused on the transformation and generation of millions of visual assets for small-to-large enterprises at scale. What You’ll Do Build and own AI-backed features end to end, from ideation to production — including layout logic, smart cropping, visual enhancement, out-painting and GenAI workflows for background fills Design scalable APIs that wrap vision models like BiRefNet, YOLOv8, Grounding DINO, SAM, CLIP, ControlNet, etc., into batch and real-time pipelines. Write production-grade Python code to manipulate and transform image data using NumPy, OpenCV (cv2), PIL, and PyTorch. Handle pixel-level transformations — from custom masks and color space conversions to geometric warps and contour ops — with speed and precision. Integrate your models into our production web app (AWS based Python/Java backend) and optimize them for latency, memory, and throughput Frame problems when specs are vague — you’ll help define what “good” looks like, and then build it Collaborate with product, UX, and other engineers without relying on formal handoffs — you own your domain What You’ll Need 2–3 years of hands-on experience with vision and image generation models such as YOLO, Grounding DINO, SAM, CLIP, Stable Diffusion, VITON, or TryOnGAN — including experience with inpainting and outpainting workflows using Stable Diffusion pipelines (e.g., Diffusers, InvokeAI, or custom-built solutions) Strong hands-on knowledge of NumPy, OpenCV, PIL, PyTorch, and image visualization/debugging techniques. 1–2 years of experience working with popular LLM APIs such as OpenAI, Anthropic, Gemini and how to compose multi-modal pipelines Solid grasp of production model integration — model loading, GPU/CPU optimization, async inference, caching, and batch processing. Experience solving real-world visual problems like object detection, segmentation, composition, or enhancement. Ability to debug and diagnose visual output errors — e.g., weird segmentation artifacts, off-center crops, broken masks. Deep understanding of image processing in Python: array slicing, color formats, augmentation, geometric transforms, contour detection, etc. Experience building and deploying FastAPI services and containerizing them with Docker for AWS-based infra (ECS, EC2/GPU, Lambda). Solid grasp of production model integration — model loading, GPU/CPU optimization, async inference, caching, and batch processing. A customer-centric approach — you think about how your work affects end users and product experience, not just model performance A quest for high-quality deliverables — you write clean, tested code and debug edge cases until they’re truly fixed The ability to frame problems from scratch and work without strict handoffs — you build from a goal, not a ticket Who You Are You’ve built systems — not just prototypes You care about both ML results and the system’s behavior in production You’re comfortable taking a rough business goal and shaping the technical path to get there You’re energized by product-focused AI work — things that users feel and rely on You’ve worked in or want to work in a startup-grade environment: messy, fast, and impactful How to apply for this opportunity? Step 1: Click On Apply! And Register or Login on our portal. Step 2: Complete the Screening Form & Upload updated Resume Step 3: Increase your chances to get shortlisted & meet the client for the Interview! About Uplers: Our goal is to make hiring reliable, simple, and fast. Our role will be to help all our talents find and apply for relevant contractual onsite opportunities and progress in their career. We will support any grievances or challenges you may face during the engagement. (Note: There are many more opportunities apart from this on the portal. Depending on the assessments you clear, you can apply for them as well). So, if you are ready for a new challenge, a great work environment, and an opportunity to take your career to the next level, don't hesitate to apply today. We are waiting for you! Show more Show less