Role: Lead AI Engineer Experience: 3+ years in AI/ML/Data Science Location: Gurgaon, work from office About Tap Health: Tap Health is a deep-tech startup transforming chronic care with AI and changing how people access health information. We build next-generation, AI-driven digital therapeutics for diabetes, PCOS, hypertension, asthma, pregnancy, obesity and more, eliminating the need for human support while significantly reducing costs, improving engagement and boosting outcomes. Tap Health's fully autonomous digital therapeutic for diabetes simplifies management by delivering real-time, daily guidance to optimise health outcomes at less than 10% of the cost of legacy products. Powered by adaptive AI and clinical protocols, it dynamically personalises each user’s care journey, delivering tailored insights, lifestyle interventions, motivational nudges, adherence support, and improved clinical outcomes. Beyond digital therapeutics, Tap Health’s Health Assistant assists users in primary symptom diagnosis based on their inputs and provides instant health advice through a seamless, voice-first experience. www.tap.health Role Overview: Lead AI Engineer - 3+ yrs exp [AI Healthcare startup] We are hiring a Lead AI Engineer in Gurgaon to drive AI-driven healthcare innovations. The ideal candidate has 3+ years of AI/ML/Data Science experience with 1+ months of GenAI production experience, and 1+ year of hands-on GenAI product development. You need to have expertise in Agentic AI deployments, causal inference, and Bayesian modelling, with a strong foundation in LLMs and traditional models. You will lead and collaborate with the AI, Engineering, and Product teams to build scalable, consumer-focused healthcare solutions. As an AI leader, you will be the go-to expert—the engineer others turn to when they hit roadblocks. You will mentor, collaborate and enable high product velocity while fostering a culture of continuous learning and innovation. Skills & Experience The ideal candidate should have the following qualities: Over 8 years of experience in AI/ML/Data Science Strong understanding of fine-tuning, optimization, and neural architectures. Hands-on experience with Python, PyTorch, and FastAI frameworks. Experience running production workloads on one or more hyperscalers (AWS, GCP, Azure, Oracle, DigitalOcean, etc.). In-depth knowledge of LLMs—how they work and their limitations. Ability to assess the advantages of fine-tuning, including dataset selection strategies. Understanding of Agentic AI frameworks, MCPs (Multi-Component Prompting), ACP (Adaptive Control Policies), and autonomous workflows. Familiarity with evaluation metrics for fine-tuned models and industry-specific public benchmarking standards in the healthcare domain. Knowledge of advanced statistical models, reinforcement learning, and Bayesian inference methods. Experience in Causal Inference and Experimental Science to improve product and marketing outcomes. Proficiency in querying and analyzing diverse datasets from multiple sources to build custom ML and optimization models. Comfortable with code reviews and standard coding practices using Python, Git, Cursor, and CodeRabbit. Show more Show less

Role: Director - Artificial Intelligence Experience: 8+ years in AI/ML/Data Science Location: Gurgaon, work from office About Tap Health: Tap Health is a deep-tech startup transforming chronic care with AI and changing how people access health information. We build next-generation, AI-driven digital therapeutics for diabetes, PCOS, hypertension, asthma, pregnancy, obesity and more, eliminating the need for human support while significantly reducing costs, improving engagement and boosting outcomes. Tap Health's fully autonomous digital therapeutic for diabetes simplifies management by delivering real-time, daily guidance to optimise health outcomes at less than 10% of the cost of legacy products. Powered by adaptive AI and clinical protocols, it dynamically personalises each user’s care journey, delivering tailored insights, lifestyle interventions, motivational nudges, adherence support, and improved clinical outcomes. Beyond digital therapeutics, Tap Health’s Health Assistant assists users in primary symptom diagnosis based on their inputs and provides instant health advice through a seamless, voice-first experience. www.tap.health Role Overview: Director - Artificial Intelligence We are hiring a full-time Director of Artificial Intelligence in Gurgaon to drive AI-driven healthcare innovations. The ideal candidate has 8+ years of AI/ML/Data Science experience with 3+ months of GenAI production experience, and 2+ year of hands-on GenAI product development. You need to have expertise in Agentic AI deployments, causal inference, and Bayesian modelling, with a strong foundation in LLMs and traditional models. You will lead and collaborate with the AI, Engineering, and Product teams to build scalable, consumer-focused healthcare solutions. As an AI leader, you will be the go-to expert—the engineer others turn to when they hit roadblocks. You will mentor, collaborate and enable high product velocity while fostering a culture of continuous learning and innovation. Skills & Experience The ideal candidate should have the following qualities: Over 8 years of experience in AI/ML/Data Science Strong understanding of fine-tuning, optimization, and neural architectures. Hands-on experience with Python, PyTorch, and FastAI frameworks. Experience running production workloads on one or more hyperscalers (AWS, GCP, Azure, Oracle, DigitalOcean, etc.). In-depth knowledge of LLMs—how they work and their limitations. Ability to assess the advantages of fine-tuning, including dataset selection strategies. Understanding of Agentic AI frameworks, MCPs (Multi-Component Prompting), ACP (Adaptive Control Policies), and autonomous workflows. Familiarity with evaluation metrics for fine-tuned models and industry-specific public benchmarking standards in the healthcare domain. Knowledge of advanced statistical models, reinforcement learning, and Bayesian inference methods. Experience in Causal Inference and Experimentation Science to improve product and marketing outcomes. Proficiency in querying and analyzing diverse datasets from multiple sources to build custom ML and optimization models. Comfortable with code reviews and standard coding practices using Python, Git, Cursor, and CodeRabbit. Show more Show less

Applied Research Center [Emerging Areas] Advanced AI [SLM, Inference Scaling, Synthetic Data, Distributed Learning, Agentic AI, ANI] New Interaction Models [Spatial computing, Mixed Reality, 3D visualizations, New Experiences] Platforms and Protocols [Architecting and engineering for Performance, Uptime, Low-latency, Scalability, Efficiency, Data, Interoperability and Low cost, Beckn, CDPI] Cybersecurity [Ethical hacking, Threat Mgmt, Supply chain security & risk, Cyber Resilience] Quantum [Quantum AI, Stack, Simulation & Optimization, Cryptography, Valued use cases] Autonomous Machines [Humanoids, Industrial Robots, Drones, Smart Products] Emerging Research [Brain, AGI, Space, Semicon ] Emerging Tech Trends Research - Research on emerging tech trends, ecosystem of players, use cases and their applicability and impact to client businesses. Scan & curate startups, universities and tech partnerships needed and create innovation ecosystem. Rapidly design and develop PoCs in Emerging tech areas. Share design specifications with other team members, get the components developed, integrate and test. Build reusable components and develop PoCs using relevant startups and Open-source solutions. 2. Thought Leadership - Develop showcases that demonstrate how emerging technologies can be applied in a business context, demo scenarios for the IP. Contribute towards patents, tier-1 publications, whitepapers, blogs in the relevant emerging tech area Get certified on the emerging technology, frameworks 3. Applied Research Center Activities - Contribute to high level design development, testing and implementation of new proof of concepts in emerging tech areas. 4. Problem Definition, Requirements - Understand technical requirements and define detailed design. Analyze the reusable components to map the given requirement to existing implementation and identify needs for enhancements 5. IP Development - Develop program level design, modular components to implement the proposed design. Design and develop reusable components. Ensure compliance with coding standards, secure coding, KM guidelines while developing the IP 6. Innovation Consulting - Understand client requirements and implement first of kind solutions using emerging tech expertise. Customize and extend IP for client specific features 7. Talent Management - Mentor the team and help them acquire the identified emerging tech skill. Participate in demo sessions, hackathons 8. Emerging Tech Startup Ecosystem – Work with startups in providing innovative solutions to client problems and augmenting Infosys offerings Technical Competencies Advanced theoretical knowledge in specific domain Experimental design and methodology expertise Data analysis and interpretation skills Prototype development capabilities Research tool proficiency relevant to domain Soft Skills and Attributes Collaborative mindset for cross-disciplinary research Communication skills for knowledge dissemination Creative problem-solving approach Intellectual curiosity and innovation focus Commercial awareness for translational research Show more Show less

Who We Are Applied Materials is the global leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. We design, build and service cutting-edge equipment that helps our customers manufacture display and semiconductor chips – the brains of devices we use every day. As the foundation of the global electronics industry, Applied enables the exciting technologies that literally connect our world – like AI and IoT. If you want to work beyond the cutting-edge, continuously pushing the boundaries of science and engineering to make possible the next generations of technology, join us to Make Possible® a Better Future. What We Offer Location: Bangalore,IND At Applied, we prioritize the well-being of you and your family and encourage you to bring your best self to work. Your happiness, health, and resiliency are at the core of our benefits and wellness programs. Our robust total rewards package makes it easier to take care of your whole self and your whole family. We’re committed to providing programs and support that encourage personal and professional growth and care for you at work, at home, or wherever you may go. Learn more about our benefits. You’ll also benefit from a supportive work culture that encourages you to learn, develop and grow your career as you take on challenges and drive innovative solutions for our customers. We empower our team to push the boundaries of what is possible—while learning every day in a supportive leading global company. Visit our Careers website to learn more about careers at Applied. Who We Are Applied Materials is the global leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. We design, build and service cutting-edge equipment that helps our customers manufacture display and semiconductor chips – the brains of devices we use every day. As the foundation of the global electronics industry, Applied enables the exciting technologies that literally connect our world – like AI and IoT. If you want to work beyond the cutting-edge, continuously pushing the boundaries of science and engineering to make possible the next generations of technology, join us to Make Possible ® a Better Future. At Applied, we prioritize your well-being and encourage you to bring your best self to work. Your happiness, health, and resiliency are at the core of our benefits and wellness programs. Our robust total rewards package makes it easier to take care of your whole self and your whole family. We’re committed to providing programs and support that encourage personal and professional growth and care for you at work, at home, or wherever you may go. Applied Materials’ Applied AI Systems Solutions (System to Materials) Business Unit is searching for a Software Engineer – AI Performance Architect to join our team! The Applied AI System to Materials team works on architecting differentiated AI Systems leveraging Applied’s fundamental innovations. Write the details of role here: Benchmark AI workloads (LLMs) in single and multi-node High Performance GPU configurations. Project and Analyze systems performance for LLMs using various parallelization techniques. Develop methodologies to measure key performance metrics and understand bottlenecks to improve efficiency. Requirements Understanding of transformer-based model architectures and basic GEMM operations. Strong programming skills in Python, C/C++. Proficiency in systems (CPU, GPU, Memory, or Network) architecture analysis and performance modelling. Experience with parallel computing architectures, interconnect fabrics and AI workloads (Finetuning/Inference). Experience with DL Frameworks (Pytorch, Tensorflow), Profiling tools (Nsight Systems, Nsight Compute, Rocprof), Containerized Environment (Docker) Applied Materials is committed to diversity in its workforce including Equal Employment Opportunity for Minorities, Females, Protected Veterans and Individuals with Disabilities. Additional Information Time Type: Full time Employee Type: Assignee / Regular Travel: Not Specified Relocation Eligible: Yes Applied Materials is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, national origin, citizenship, ancestry, religion, creed, sex, sexual orientation, gender identity, age, disability, veteran or military status, or any other basis prohibited by law. Show more Show less

Company Description UAE-based ZySec AI provides cutting-edge cybersecurity solutions to help enterprises tackle evolving security challenges at scale. Utilizing an autonomous AI workforce, ZySec AI enhances operational efficiency by automating repetitive, resource-intensive tasks, enabling security teams to focus on strategic priorities. Our mission is to make AI more efficient, accessible, and private for security professionals.mWe're building the future of Autonomous Data Intelligence at CyberPod AI and were looking for a deeply technical, hands-on AI Engineer to push the boundaries of whats possible with Large Language Models (LLMs). This role is for someone whos already been in the trenches: fine-tuned foundation models, experimented with quantization and performance tuning, and knows PyTorch inside out. If youre passionate about optimizing LLMs, crafting efficient reasoning architectures, and contributing to open-source communities like Hugging Face, this is your playground. Role Description Fine-tune Large Language Models (LLMs) on custom datasets for specialized reasoning tasks. Design and run benchmarking pipelines across accuracy, speed, token throughput, and energy efficiency. Implement quantization, pruning, and distillation techniques for model compression and deployment readiness. Evaluate and extend agentic RAG (Retrieval-Augmented Generation) pipelines and reasoning agents. Contribute to SOTA model architectures for multi-hop, temporal, and multimodal reasoning. Collaborate closely with the data engineering, infra, and applied research teams to bring ideas from paper to production. Own and drive experiments, ablations, and performance dashboards end-to-end. Requirements Hands-on experience working with deep learning and large models, particularly LLMs. Strong understanding of PyTorch internals: autograd, memory profiling, efficient dataloaders, mixed precision. Proven track record in fine-tuning LLMs (e.g., LLaMA, Falcon, Mistral, Open LLaMA, T5, etc.) on real-world use cases. Benchmarking skills: can run standardized evals (e.g., MMLU, GSM8K, HELM, TruthfulQA) and interpret metrics. Deep familiarity with quantization techniques: GPTQ, AWQ, QLoRA, bitsandbytes, and low-bit inference. Working knowledge of Hugging Face ecosystem (Transformers, Accelerate, Datasets, Evaluate). Active Hugging Face profile with at least one public model/repo published. Experience in training and optimizing multi-modal models (vision-language/audio) is a big plus. Published work (arXiv, GitHub, blogs) or open-source contributions preferred. If you are passionate about AI and want to be a part of a dynamic and innovative team, then ZySec AI is the perfect place for you. Apply now and join us in shaping the future of artificial intelligence. Show more Show less

Description The role is based in Munich, Germany (this is not a remote opportunity). We offer immigration and relocation support. The vision of the Ontology Product Knowledge Team is to provide a standardized, semantically rich, easily discoverable, extensible, and universally applicable body of product knowledge that can be consistently utilized across customer shopping experiences, selling partner listing experiences and internal enrichment of product data. We aim to make product knowledge compelling, easy to use, and feature rich. Our work to build comprehensive product knowledge allows us to semantically understand a customer’s intent – whether that is a shopping mission or a seller offering products. We strive to make these experiences more intuitive for all customers. As an Ontologist, you work on a global team of knowledge builders to deliver world-class, intuitive, and comprehensive taxonomy and ontology models to optimize product discovery for Amazon web and mobile experiences. You collaborate with business partners and engineering teams to deliver knowledge-based solutions to enable product discoverability for customers. In this role, you will directly impact the customer experience as well as the company’s product knowledge foundation. Tasks And Responsibilities Develop logical, semantically rich, and extensible data models for Amazon's extensive product catalog Ensure our ontologies provide comprehensive domain coverage that are available for both human and machine ingestion and inference Create new schema using Generative Artificial Intelligence (generative AI) models Analyze website metrics and product discovery behaviors to make data-driven decisions on optimizing our knowledge graph data models globally Expand and refine the expansion of data retrieval techniques to utilize our extensive knowledge graph Contribute to team goal setting and future state vision Drive and coordinate cross-functional projects with a broad range of merchandisers, engineers, designers, and other groups that may include architecting new data solutions Develop team operational excellence programs, data quality initiatives and process simplifications Evangelize ontology and semantic technologies within and across teams at Amazon Develop and refine data governance and processes used by global Ontologists Mentor and influence peers Inclusive Team Culture: Our team has a global presence: we celebrate diverse cultures and backgrounds within our team and our customer base. We are committed to furthering our culture of inclusion, offering continuous access to internal affinity groups as well as highlighting diversity programs. Work/Life Harmony: Our team believes that striking the right balance between work and your outside life is key. Our work is not removed from everyday life, but instead is influenced by it. We offer flexibility in working hours and will work with you to facilitate your own balance between your work and personal life. Career Growth: Our team cares about your career growth, from your initial company introduction and training sessions, to continuous support throughout your entire career at Amazon. We recognize each team member as an individual, and we will build on your skills to help you grow. We have a broad mix of experience levels and tenures, and we are building an environment that celebrates knowledge sharing. Perks You will have the opportunity to support CX used by millions of customers daily and to work with data at a scale very few companies can offer. We have offices around the globe, and have the opportunity to be considered for global placement. You’ll receive on the job training and group development opportunities. Basic Qualifications Degree in Library Science, Information Systems, Linguistics or equivalent professional experience 5+ years of relevant work experience working in ontology and/or taxonomy roles Proven skills in data retrieval and data research techniques Ability to quickly understand complex processes and communicate them in simple language Experience creating and communicating technical requirements to engineering teams Ability to communicate to senior leadership (Director and VP levels) Experience with generative AI (e.g. creating prompts) Knowledge of Semantic Web technologies (RDF/s, OWL), query languages (SPARQL) and validation/reasoning standards (SHACL, SPIN) Knowledge of open-source and commercial ontology engineering editors (e.g. Protege, TopQuadrant products, PoolParty) Detail-oriented problem solver who is able to work in fast-changing environment and manage ambiguity Proven track record of strong communication and interpersonal skills Proficient English language skills Preferred Qualifications Master’s degree in Library Science, Information Systems, Linguistics or other relevant fields Experience building ontologies in the e-commerce and semantic search spaces Experience working with schema-level constructs (e.g. higher-level classes, punning, property inheritance) Proficiency in SQL, SPARQL Familiarity with software engineering life cycle Familiarity with ontology manipulation programming libraries Exposure to data science and/or machine learning, including graph embedding Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner. Company - Amazon Dev Center India - Hyderabad - A85 Job ID: A2837060 Show more Show less

At PwC, our people in data and analytics engineering focus on leveraging advanced technologies and techniques to design and develop robust data solutions for clients. They play a crucial role in transforming raw data into actionable insights, enabling informed decision-making and driving business growth. Those in intelligent automation at PwC will focus on conducting process mining, designing next generation small- and large-scale automation solutions, and implementing intelligent process automation, robotic process automation and digital workflow solutions to help clients achieve operational efficiencies and reduce costs. Focused on relationships, you are building meaningful client connections, and learning how to manage and inspire others. Navigating increasingly complex situations, you are growing your personal brand, deepening technical expertise and awareness of your strengths. You are expected to anticipate the needs of your teams and clients, and to deliver quality. Embracing increased ambiguity, you are comfortable when the path forward isn’t clear, you ask questions, and you use these moments as opportunities to grow. Skills Examples of the skills, knowledge, and experiences you need to lead and deliver value at this level include but are not limited to: Respond effectively to the diverse perspectives, needs, and feelings of others. Use a broad range of tools, methodologies and techniques to generate new ideas and solve problems. Use critical thinking to break down complex concepts. Understand the broader objectives of your project or role and how your work fits into the overall strategy. Develop a deeper understanding of the business context and how it is changing. Use reflection to develop self awareness, enhance strengths and address development areas. Interpret data to inform insights and recommendations. Uphold and reinforce professional and technical standards (e.g. refer to specific PwC tax and audit guidance), the Firm's code of conduct, and independence requirements. Design, develop, and maintain data pipelines and ETL processes for GenAI projects. Collaborate with data scientists and software engineers to implement machine learning models and algorithms. Optimize data infrastructure and storage solutions to ensure efficient and scalable data processing. Implement event-driven architectures to enable real-time data processing and analysis. Utilize containerization technologies like Kubernetes and Docker for efficient deployment and scalability. Develop and maintain data lakes for storing and managing large volumes of structured and unstructured data. Implement and integrate LLM frameworks (Langchain, Semantic Kernel) for advanced language processing and analysis. Collaborate with cross-functional teams to design and implement solution architectures for GenAI projects. Utilize cloud computing platforms such as Azure or AWS for data processing, storage, and deployment. Monitor and troubleshoot data pipelines and systems to ensure smooth and uninterrupted data flow. Stay up-to-date with the latest advancements in GenAI technologies and recommend innovative solutions to enhance data engineering processes. Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions. Document data engineering processes, methodologies, and best practices. Maintain solution architecture certificates and stay current with industry best practices. Requirements Python Proficiency: Minimum 3 years of hands-on experience building applications with Python. Scalable System Design: Solid understanding of designing and architecting scalable Python applications, particularly for Gen AI use cases, with a strong understanding of various components and systems architecture patterns to make cohesive and decoupled, scalable applications. Web Frameworks: Familiarity with Python web frameworks (Flask, FastAPI) for building web applications around AI models. Modular Design & Security: Demonstrated ability to design applications with modularity, reusability, and security best practices in mind (session management, vulnerability prevention, etc.,). Cloud-Native Development: Familiarity with cloud-native development patterns and tools (e.g., REST APIs, microservices, serverless functions). Cloud Deployments: Experience deploying and managing containerized applications on Azure/AWS (Azure Kubernetes Service, Azure Container Instances, or similar). Version Control (Git): Strong proficiency in Git for effective code collaboration and management. CI/CD: Knowledge of continuous integration and deployment (CI/CD) practices on cloud platforms. 3-5 years of relevant technical/technology experience, with a focus on GenAI projects. Strong programming skills in Python. Experience with data processing frameworks like Apache Spark or similar. Proficiency in SQL and database management systems. Preferred Skills Gen AI Frameworks: Experience with LLM frameworks or tools for interacting with LLMs such as LangChain, Semantic Kernel, LlamaIndex Data Pipelines: Experience in setting up data pipelines for model training and real-time inference. If you are passionate about GenAI technologies and have a proven track record in data engineering, join PwC US-Acceleration Center and be part of a dynamic team that is shaping the future of GenAI solutions. We offer a collaborative and innovative work environment where you can make a significant impact. Show more Show less

A career within our Infrastructure practice will provide you with the opportunity to design, build, coordinate and maintain the IT environments for clients to run internal operations, collect data, monitor, develop and launch products. Infrastructure management consists of hardware, storage, compute, network and software layers. As a part of our Infrastructure Engineering team, you will be responsible for maintaining the critical IT systems which includes build, run and maintenance while providing technical support and training that aligns to industry leading practices. To really stand out and make us fit for the future in a constantly changing world, each and every one of us at PwC needs to be a purpose-led and values-driven leader at every level. To help us achieve this we have the PwC Professional; our global leadership development framework. It gives us a single set of expectations across our lines, geographies and career paths, and provides transparency on the skills we need as individuals to be successful and progress in our careers, now and in the future. Responsibilities As a Senior Associate, you'll work as part of a team of problem solvers, helping to solve complex business issues from strategy to execution. PwC Professional skills and responsibilities for this management level include but are not limited to: Use feedback and reflection to develop self awareness, personal strengths and address development areas. Delegate to others to provide stretch opportunities, coaching them to deliver results. Demonstrate critical thinking and the ability to bring order to unstructured problems. Use a broad range of tools and techniques to extract insights from current industry or sector trends. Review your work and that of others for quality, accuracy and relevance. Know how and when to use tools available for a given situation and can explain the reasons for this choice. Seek and embrace opportunities which give exposure to different situations, environments and perspectives. Use straightforward communication, in a structured way, when influencing and connecting with others. Able to read situations and modify behavior to build quality relationships. Uphold the firm's code of ethics and business conduct. AI Engineer Overview We are seeking an exceptional AI Engineer to drive the development, optimization, and deployment of cutting-edge generative AI solutions for our clients. This role is at the forefront of applying generative models to solve real-world business challenges, requiring deep expertise in both the theoretical underpinnings and practical applications of generative AI. Core Qualifications Advanced degree (MS/PhD) in Computer Science, Machine Learning, or related field with a focus on generative models 3+ years of hands-on experience developing and deploying AI models in production environments with 1 year of experience in developing generative AI pilots, proofs of concept, and prototypes Deep understanding of state-of-the-art AI architectures (e.g., Transformers, VAEs, GANs, Diffusion Models) Expertise in PyTorch or TensorFlow, with a preference for experience in both Proficiency in Python and software engineering best practices for AI systems Technical Skills Required Demonstrated experience with large language models (LLMs) such as GPT, BERT, T5, etc. Practical understanding of generative AI frameworks (e.g., Hugging Face Transformers, OpenAI GPT, DALL-E) Familiarity with prompt engineering and few-shot learning techniques Expertise in MLOps and LLMOps practices, including CI/CD for ML models Strong knowledge of one or more cloud-based AI services (e.g., AWS SageMaker, Azure ML, Google Vertex AI) Preferred Proficiency in optimizing generative models for inference (quantization, pruning, distillation) Experience with distributed training of large-scale AI models Experience with model serving technologies (e.g., TorchServe, TensorFlow Serving, Triton Inference Server) Key Responsibilities Architect and implement end-to-end generative AI solutions, from data preparation to production deployment Develop custom AI models and fine-tune pre-trained models for specific client use cases Optimize generative models for production, balancing performance, latency, and resource utilization Design and implement efficient data pipelines for training and serving generative models Develop strategies for effective prompt engineering and few-shot learning in production systems Implement robust evaluation frameworks for generative AI outputs Collaborate with cross-functional teams to integrate generative AI capabilities into existing systems Address challenges related to bias, fairness, and ethical considerations in generative AI applications Project Delivery Lead the technical aspects of generative AI projects from pilot to production Develop proof-of-concepts and prototypes to demonstrate the potential of generative AI in solving client problems Conduct technical feasibility studies for applying generative AI to novel use cases Implement monitoring and observability solutions for deployed generative models Troubleshoot and optimize generative AI systems in production environments Client Engagement Provide expert technical guidance on generative AI capabilities and limitations to clients Collaborate with solution architects to design generative AI-powered solutions that meet client needs Present technical approaches and results to both technical and non-technical stakeholders Assist in scoping and estimating generative AI projects Innovation and Knowledge Sharing Stay at the forefront of generative AI research and industry trends Contribute to the company's intellectual property through patents or research publications Develop internal tools and frameworks to accelerate generative AI development Mentor junior team members on generative AI technologies and best practices Contribute to technical blog posts and whitepapers on generative AI applications The ideal candidate will have a proven track record of successfully deploying AI models in production environments, a deep understanding of the latest advancements in generative AI, and the ability to apply this knowledge to solve complex business problems. They should be passionate about pushing the boundaries of what's possible with generative AI and excited about the opportunity to shape the future of AI-driven solutions for our clients. Show more Show less

Job Description: Role Overview :- Monitor, evaluate, and optimize AI/LLM workflows in production environments. Ensure reliable, efficient, and high-quality AI system performance by building out an LLM Ops platform that is self-serve for the engineering and data science departments. Key Responsibilities:- Collaborate with data scientists and software engineers to integrate an LLM Ops platform (Opik by CometML) for existing AI workflows Identify valuable performance metrics (accuracy, quality, etc) for AI workflows and create on-going sampling evaluation processes using the LLM Ops platform that alert when metrics drop below thresholds Cross-team collaboration to create datasets and benchmarks for new AI workflows Run experiments on datasets and optimize performance via model changes and prompt adjustments Debug and troubleshoot AI workflow issues Optimize inference costs and latency while maintaining accuracy and quality Develop automations for LLM Ops platform integration to empower data scientists and software engineers to self-serve integration with the AI workflows they build Requirements:- Strong Python programming skills Experience with generative AI models and tools (OpenAI, Anthropic, Bedrock, etc) Knowledge of fundamental statistical concepts and tools in data science such as: heuristic and non-heuristic measurements in NLP (BLEU, WER, sentiment analysis, LLM-as-judge, etc), standard deviation, sampling rate, and a high level understanding of how modern AI models work (knowledge cutoffs, context windows, temperature, etc) Familiarity with AWS Understanding of prompt engineering concepts People skills: you will be expected to frequently collaborate with other teams to help to perfect their AI workflows Experience Level 3-5 years of experience in LLM/AI Ops, MLOps, Data Science, or MLE Pattern is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. Show more Show less

Job Requisition ID # 25WD85491 Position Overview We are looking for an experienced Principal Software Engineer to join our platform team focusing on AI/ML Platform (AMP). This team builds and maintains central components to fast track the development of new ML/AI models such as model development studio, feature store, model serving and model observability. The ideal candidate would have a background in ML Ops, Data engineering and DevOps with the experience of building high scale deployment architectures and observability. As an important contributor to our engineering team, you will help shape the future of our AI/ML capabilities, delivering solutions that inspire value for our organization. You will report directly to an Engineering Manager, and you will be based in Pune. Responsibilities System design: You will design, implement and manage software systems for the AI/ML Platform and orchestrate the full ML development lifecycle for the partner teams Mentoring: Spreading your knowledge, sharing best practices and doing design reviews to step up the expertise at the team level Multi-cloud architecture: Define components which leverages strengths from multiple cloud platforms (e.g., AWS, Azure) to optimize performance, cost, and scalability AI/ML observability: You will build systems for monitoring performance of AI/ML models and find insights on the underlying data such as drift detection, data fairness/bias and anomalies ML Solution Deployment: You will develop tools for building and deploying ML artefacts in production environments and facilitating a smooth transition from development to deployment Big Data Management: Automate and orchestrate tasks related to managing big data transformation and processing and build large-scale data stores for ML artifacts Scalable Services: Design and implement low-latency, scalable prediction, and inference services to support the diverse needs of our users Cross-Functional Collaboration: Collaborate across diverse teams, including machine learning researchers, developers, product managers, software architects, and operations, fostering a collaborative and cohesive work environment End-to-end ownership: You will take the end-to-end ownership of the components and work with other engineers in the team including design, architecture, implementation, rollout and onboarding support to partner teams, production on-call support, testing/verification, investigations etc Minimum Qualifications Educational Background: Bachelor’s degree in Computer Science or equivalent practical experience Experience: Over 8 years of experience in software development and engineering, delivering production systems and services Prior experience of working with MLOps team at the intersection of the expertise across ML model deployments, DevOps and data engineering Hands-on skills: Ability to fluently translate the design into high quality code in golang, python, Java Knowledge of DevOps practices, containerization, orchestration tools such as CI/CD, Terraform, Docker, Kubernetes, Gitops Demonstrate knowledge of distributed data processing frameworks, orchestrators, and data lake architectures using technologies such as Spark, Airflow, iceberg/ parquet formats Prior collaborations with Data science teams to deploy their models, setting up ML observability for inference level monitoring Exposure for building RAG based applications by collaborating with other product teams, Data scientists/AI engineers Demonstrate creative problem-solving skills with the ability to break down problems into manageable components Knowledge of Amazon AWS and/or Azure cloud for solutioning large scale application deployments Excellent communication and collaboration skills, fostering teamwork and effective information exchange Preferred Qualifications Experience in integrating with third party vendors Experience in latency optimization with the ability to diagnose, tune, and enhance the efficiency of serving systems Familiarity with tools and frameworks for monitoring and managing the performance of AI/ML models in production (e.g., MLflow, Kubeflow, TensorBoard) Familiarity with distributed model training/inference pipelines using (KubeRay or equivalent) Exposure to leveraging GPU computing for AI/ML workloads, including experience with CUDA, OpenCL, or other GPU programming tools, to significantly enhance model training and inference performance Exposure to ML libraries such as PyTorch, TensorFlow, XGBoost, Pandas, and ScikitLearn Learn More About Autodesk Welcome to Autodesk! Amazing things are created every day with our software – from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made. We take great pride in our culture here at Autodesk – our Culture Code is at the core of everything we do. Our values and ways of working help our people thrive and realize their potential, which leads to even better outcomes for our customers. When you’re an Autodesker, you can be your whole, authentic self and do meaningful work that helps build a better future for all. Ready to shape the world and your future? Join us! Salary transparency Salary is one part of Autodesk’s competitive compensation package. Offers are based on the candidate’s experience and geographic location. In addition to base salaries, we also have a significant emphasis on discretionary annual cash bonuses, commissions for sales roles, stock or long-term incentive cash grants, and a comprehensive benefits package. Diversity & Belonging We take pride in cultivating a culture of belonging and an equitable workplace where everyone can thrive. Learn more here: https://www.autodesk.com/company/diversity-and-belonging Are you an existing contractor or consultant with Autodesk? Please search for open jobs and apply internally (not on this external site). Show more Show less

Job Category: AIML Job Type: Full Time Job Location: Bengaluru Mangalore Experience: 4-8 Years Skills: AI AWS/AZURE/GCP Azure ML C computer vision data analytics Data Modeling Data Visualization deep learning Descriptive Analytics GenAI Image processing Java LLM models ML ONNX Predictive Analytics Python R Regression/Classification Models SageMaker SQL TensorFlow Position Overview We are looking for an experienced AI/ML Engineer to join our team in Bengaluru. The ideal candidate will bring a deep understanding of machine learning, artificial intelligence, and big data technologies, with proven expertise in developing scalable AI/ML solutions. You will lead technical efforts, mentor team members, and collaborate with cross-functional teams to design, develop, and deploy cutting edge AI/ML applications. Job Details Job Category: AI/ML Engineer. Job Type: Full-Time Job Location: Bengaluru Experience Required: 4-8 Years About Us We are a multi-award-winning creative engineering company. Since 2011, we have worked with our customers as a design and technology enablement partner, guiding them on their digital transformation journeys. Roles And Responsibilities Design, develop, and deploy deep learning models for object classification, detection, and segmentation using CNNs and Transfer Learning. Implement image preprocessing and advanced computer vision pipelines. Optimize deep learning models using pruning, quantization, and ONNX for deployment on edge devices. Work with PyTorch, TensorFlow, and ONNX frameworks to develop and convert models. Accelerate model inference using GPU programming with CUDA and cuDNN. Port and test models on embedded and edge hardware platforms. ( Orin, Jetson, Hailo ) Conduct research and experiments to evaluate and integrate GenAI technologies in computer vision tasks. Explore and implement cloud-based AI workflows, particularly using AWS/Azure AI/ML services. Collaborate with cross-functional teams for data analytics, data processing, and large-scale model training. Required Skills Strong programming experience in Python. Solid background in deep learning, CNNs, and transfer learning and Machine learning basics. Expertise in object detection, classification, segmentation. Proficiency with PyTorch, TensorFlow, and ONNX. Experience with GPU acceleration (CUDA, cuDNN). Hands-on knowledge of model optimization (pruning, quantization). Experience deploying models to edge devices (e.g., Jetson, mobile, Orin, Hailo ) Understanding of image processing techniques. Familiarity with data pipelines, data preprocessing, and data analytics. Willingness to explore and contribute to Generative AI and cloud-based AI solutions. Good problem-solving and communication skills. Preferred (Nice-to-Have) Experience with C/C++. Familiarity with AWS Cloud AI/ML tools (e.g., SageMaker, Rekognition). Exposure to GenAI frameworks like OpenAI, Stable Diffusion, etc. Knowledge of real-time deployment systems and streaming analytics. Qualifications Graduation/Post-graduation in Computers, Engineering, or Statistics from a reputed institute. What We Offer Competitive salary and benefits package. Opportunity to work in a dynamic and innovative environment. Professional development and learning opportunities. Visit us on: CodeCraft Technologies LinkedIn : CodeCraft Technologies LinkedIn Instagram : CodeCraft Technologies Instagram Show more Show less

Job Description GalaxEye Space, is a deep-tech Space start-up spun off from IIT-Madras and is currently based in Bengaluru, Karnataka. We are dedicated to advancing the frontiers of space exploration. Our mission is to develop cutting-edge solutions that address the challenges of the modern space industry by specialising in developing a constellation of miniaturised, multi-sensor SAR+EO satellites. Our new age technology enables all-time, all-weather imaging, this with leveraging advanced processing and AI capabilities, we ensure near real-time data delivery and are glad to highlight that we have successfully demonstrated these imaging capabilities, the first of its kind in the world, across various platforms such as Drones as well as HAPS (High-Altitude Pseudo Satellites). Responsibilities Architect and maintain the build pipeline that converts R&D Python notebooks into immutable, versioned executables and libraries Optimize the Python codes for extracting maximum GPU performance Define and enforce coding standards, branching strategy, semantic release tags, and artifact-signing process Lead a team of full-stack developers to integrate Python inference services with the React-Electron UI via gRPC/REST contracts Stand-up and maintain an offline replica environment (VM or bare- metal) that mirrors the forward-deployed system; gate releases through this environment in CI Own automated test suites: unit, contract, regression, performance, and security scanning Coordinate multi-iteration hand-offs with forward engineers; triage returned diffs, merge approved changes, and publish patched releases Mentor the team, conduct code & design reviews, and drivecontinuous-delivery best practices in an air-gap-constrained context Requirements 5+ yrs in software engineering with at least 2 yrs technical-lead experience Deep Python expertise (packaging, virtualenv/venv, dependency pinning) and solid JavaScript/TypeScript skills for React-Electron CI/CD mastery (GitHub Actions, Jenkins, GitLab CI) with artifact repositories (Artifactory/Nexus) and infrastructure-as-code (Packer, Terraform, Ansible) Strong grasp of cryptographic signing, checksum verification, and secure supply-chain principles Experience releasing software to constrained or disconnected environments Additional Skills Knowledge of containerization (Docker/Podman) and offline image distribution Prior work on remote-sensing or geospatial analytics products Benefits Acquire valuable opportunities for learning and development through close collaboration with the founding team. Contribute to impactful projects and initiatives that drive meaningful change. We provide a competitive salary package that aligns with your expertise and experience. Enjoy comprehensive health benefits, including medical, dental, and vision coverage, ensuring the well-being of you and your family. Work in a dynamic and innovative environment alongside a dedicated and passionate team. check(event) ; career-website-detail-template-2 => apply(record.id,meta)" mousedown="lyte-button => check(event)" final-style="background-color:#5BBD6E;border-color:#5BBD6E;color:white;" final-class="lyte-button lyteBackgroundColorBtn lyteSuccess" lyte-rendered=""> Show more Show less

When you join Verizon You want more out of a career. A place to share your ideas freely even if theyre daring or different. Where the true you can learn, grow, and thrive. At Verizon, we power and empower how people live, work and play by connecting them to what brings them joy. We do what we love driving innovation, creativity, and impact in the world. Our V Team is a community of people who anticipate, lead, and believe that listening is where learning begins. In crisis and in celebration, we come together lifting our communities and building trust in how we show up, everywhere & always. Want in? Join the V Team Life. What Youll Be Doing... Designing and Implementing ML Model pipelines (Batch and real-time) for efficient model training and serving/inference. Implementing and analyzing the performance of advanced algorithms (Specifically Deep Learning based ML Models). Solving the model inferencing failures/fallouts. Optimizing existing machine-learning Model Pipelines to ensure the training/inferencing is within the standard duration. Collaborating effectively with cross-functional teams to understand business needs and deliver impactful solutions. Contributing to developing robust and scalable distributed computing systems for large-scale data processing. Designing, developing, and implementing innovative AI/ML solutions using Python, CI/CD, public cloud platforms. Implementing model performance metrics pipeline for predictive models, covering different types of algorithms to adhere to Responsible AI. What were looking for... Youll need to have: Bachelor's degree or four or more years of work experience. Four or more years of relevant work experience. Experience in Batch Model Inferencing, Model-serving in Realtime. Knowledge on Frameworks such as BentoML TensorFlow Serving (TFX) or Triton. Solid expertise on GCP Cloud ML techstacks such as Bigquery, Data Proc, Airflow, Cloud Functions, Spanner, Data Flow. Very good experience on languages such as Python and PySpark. Expertise on Distributed computation and Multi-node distributed model training. Good understanding on GPU usage management. Experience on RAY Core and RAY Serve (batch and real-time models). Experience in CI/CD practices. Even better if you have one or more of the following: GCP Certifications or any Cloud Certification on AI/ML or Data. If Verizon and this role sound like a fit for you, we encourage you to apply even if you dont meet every even better qualification listed above. Where youll be working In this hybrid role, you'll have a defined work location that includes work from home and assigned office days set by your manager. Scheduled Weekly Hours 40 Diversity and Inclusion Were proud to be an equal opportunity employer. At Verizon, we know that diversity makes us stronger. We are committed to a collaborative, inclusive environment that encourages authenticity and fosters a sense of belonging. We strive for everyone to feel valued, connected, and empowered to reach their potential and contribute their best. Check out our diversity and inclusion page to learn more. Locations Bangalore, India Hyderabad, India Chennai, India Show more Show less

Position: AI/ML Engineer (Python AWS REST APIs) Experience 3 to 5 Years Location: Indore Work from office Job Summary We are seeking a passionate AI/ML Engineer to join our team in building the core AI-driven functionality of an intelligent visual data encryption system. The role involves designing, training, and deploying AI models (e.g., CLIP, DCGANs, Decision Trees), integrating them into a secure backend, and operationalizing the solution via AWS cloud services and Python-based APIs. Responsibilities AI/ML Development Design and train deep learning models for image classification and sensitivity tagging using CLIP, DCGANs, and Decision Trees. Build synthetic datasets using DCGANs for balancing. Fine-tune pre-trained models for customized encryption logic. Implement explainable classification logic for model outputs. Validate model performance using custom metrics and datasets. API Development Design and develop Python RESTful APIs using FastAPI or Flask for: Image upload and classification Model inference endpoints Encryption trigger calls Integrate APIs with AWS Lambda and Amazon API Gateway. AWS Integration Deploy and manage AI models on Amazon SageMaker for training and real-time inference. Use AWS Lambda for serverless backend compute. Store encrypted image data on Amazon S3 and metadata on Amazon RDS (PostgreSQL). Use AWS Cognito for secure user authentication and KMS for key management. Monitor job status via CloudWatch and enable secure, scalable API access. Required Skills & Experience: Must-Have 35 years of experience in AI/ML (especially vision-based systems). Strong experience with PyTorch or TensorFlow for model development. Proficient in Python with experience building RESTful APIs. Hands-on experience with Amazon SageMaker, Lambda, API Gateway, and S3. Knowledge of OpenSSL/PyCryptodome or basic cryptographic concepts. Understanding of model deployment, serialization, and performance tuning. Nice-to-Have Experience with CLIP model fine-tuning. Familiarity with Docker, GitHub Actions, or CI/CD pipelines. Experience in data classification under compliance regimes (e.g., GDPR, HIPAA). Familiarity with multi-tenant SaaS design patterns. Tools & Technologies: Python, PyTorch, TensorFlow FastAPI, Flask AWS: SageMaker, Lambda, S3, RDS, Cognito, API Gateway, KMS Git, Docker, Postgres, OpenCV, OpenSSL Note: For I-VDES Project. Excellent communication and interpersonal skills Ability to work with tight deadlines Kindly share your resume on hr@advantal.net Show more Show less

Summary Gainwell is seeking LLM Ops Engineers and ML Ops Engineers to join our growing AI/ML team. This role is responsible for developing, deploying, and maintaining scalable infrastructure and pipelines for Machine Learning (ML) models and Large Language Models (LLMs). You will play a critical role in ensuring smooth model lifecycle management, performance monitoring, version control, and compliance while collaborating closely with Data Scientists, DevOps, and Role Description Core LLM Ops Responsibilities: Develop and manage scalable deployment strategies specifically tailored for LLMs (GPT, Llama, Claude, etc.). Optimize LLM inference performance, including model parallelization, quantization, pruning, and fine-tuning pipelines. Integrate prompt management, version control, and retrieval-augmented generation (RAG) pipelines. Manage vector databases, embedding stores, and document stores used in conjunction with LLMs. Monitor hallucination rates, token usage, and overall cost optimization for LLM APIs or on-prem deployments. Continuously monitor models for its performance and ensure alert system in place. Ensure compliance with ethical AI practices, privacy regulations, and responsible AI guidelines in LLM workflows. Core ML Ops Responsibilities: Design, build, and maintain robust CI/CD pipelines for ML model training, validation, deployment, and monitoring. Implement version control, model registry, and reproducibility strategies for ML models. Automate data ingestion, feature engineering, and model retraining workflows. Monitor model performance, drift, and ensure proper alerting systems are in place. Implement security, compliance, and governance protocols for model deployment. Collaborate with Data Scientists to streamline model development and experimentation. What We’re Looking For Bachelor's or Master's degree or higher in Computer Science, Data Sciences-Machine Learning, Engineering, or related fields. Strong experience with ML Ops tools (Kubeflow, ML flow, TFX, Sage Maker, etc.). Experience with LLM-specific tools and frameworks ( LangChain, Lang Graph, LlamaIndex, Hugging Face, OpenAI APIs, Vector DBs like Pinecone, FAISS, Weavite, Chroma DB etc.). Solid experience in deploying models in cloud (AWS, Azure, GCP) and on-prem environments. Proficient in containerization (Docker, Kubernetes) and CI/CD practices. Familiarity with monitoring tools like Prometheus, Grafana, and ML observability platforms. Strong coding skills in Python, Bash, and familiarity with infrastructure-as-code tools (Terraform, Helm, etc.).Knowledge of healthcare AI applications and regulatory compliance (HIPAA, CMS) is a plus. Strong skills in Giskard, Deepeval etc. Qualifications Bachelor or Masters or Higher in Computer Sciences, Data Sciences, or any related field 3+ years to 7 Years of experience in deploying ML/DL and LLM based solutions in large scale deployment environment or related experience Experience with fine-tuning LLMs and serving them in production at scale. Knowledge of model compression techniques for LLMs (LoRA, QLoRA, quantization-aware training). Experience with distributed systems and high-performance computing for large-scale model serving. Awareness of AI fairness, explainability, and governance frameworks. What You Should Expect in This Role Fully Remote Opportunity – Work from anywhere in the U.S. / India Minimal Travel Required – Occasional travel opportunities (0-10%). Opportunity to Work on Cutting-Edge AI Solutions in a mission-driven healthcare technology environment. Show more Show less

Introduction A career in IBM Consulting is rooted by long-term relationships and close collaboration with clients across the globe. You'll work with visionaries across multiple industries to improve the hybrid cloud and AI journey for the most innovative and valuable companies in the world. Your ability to accelerate impact and make meaningful change for your clients is enabled by our strategic partner ecosystem and our robust technology platforms across the IBM portfolio; including Software and Red Hat. Curiosity and a constant quest for knowledge serve as the foundation to success in IBM Consulting. In your role, you'll be encouraged to challenge the norm, investigate ideas outside of your role, and come up with creative solutions resulting in ground breaking impact for a wide network of clients. Our culture of evolution and empathy centers on long-term career growth and development opportunities in an environment that embraces your unique skills and experience Role Overview Your role and responsibilities Hiring an ML Engineer with experience in Cloudera ML to support end-to-end model development, deployment, and monitoring on the CDP platform. Key Responsibilities Develop and deploy models using CML workspaces Build CI/CD pipelines for ML lifecycle Integrate with governance and monitoring tools Enable secure model serving via REST APIs Preferred Education Master's Degree Skills Required Required technical and professional expertise Experience in Cloudera ML, Spark MLlib, or scikit-learn ML pipeline automation (MLflow, Airflow, or equivalent) Model governance, lineage, and versioning API exposure for real-time inference Show more Show less

Job Description We have an exciting and rewarding opportunity for you to take your software engineering career to the next level. As a Software Engineer III at JPMorgan Chase within the Consumer & Community Banking, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives. Job Responsibilities Design and implement highly scalable and reliable data processing pipelines and deploy model inference services. Deploy solutions into public cloud (AWS or Azure) infrastructure. Experiment, develop and productionize high quality machine learning models, services, and platforms to make a huge technology and business impact. Write code to create several machine learning experimentation pipelines. Design and implement feature engineering pipelines and push them to feature stores. Analyze large datasets to extract actionable insights and drive data-driven decision-making. Ensure the scalability and reliability of AI/ML solutions in a production environment. Required Qualifications, Capabilities, And Skills Formal training or certification on software engineering concepts and 3+ years applied experience Proficient in coding in Javascript, ReactJS, HTML and CSS. Proven experience as a front-end developer with a strong focus on ReactJS and Typescript. Technical feasibility of UI/UX designs and optimize applications for maximum speed and scalability Proficiency in programming languages such as Python, Java etc. Full-stack experience API development, including JavaScript frameworks such as React, would be highly valuable Experience in using GenAI (OpenAI or AWS Bedrock) to solve business problem. Experience with large scale training, validation and testing Experience and skills in training and deploying ML models on AWS SageMaker or Bedrock Experience in machine learning frameworks such as TensorFlow, PyTorch, Pytorch Keras, or Scikit-learn. Familiarity with cloud platforms (AWS) and containerization technologies (Docker, Kubernetes, Amazon EKS, ECS). Preferred Qualifications, Capabilities, And Skills Expert in at least one of the following areas: Natural Language Processing, Reinforcement Learning, Ranking and Recommendation, or Time Series Analysis. Knowledge of machine learning frameworks: Pytorch, Keras, MXNet, Scikit-Learn, as well as LLM frameworks, such as LangChain, LangGraph, etc Understanding of finance or investment banking businesses is an added advantage ABOUT US Show more Show less

We are seeking AI Architect to lead the design, development, and deployment of advanced AI systems, with a strong emphasis on Large Language Models (LLMs) , fine-tuning , and customer experience (CX) technologies . This role blends deep technical expertise with leadership, research, and infrastructure planning to deliver intelligent, scalable, and customer-centric AI solutions across cloud and on-premise environments. Key Responsibilities 1. LLM Development & Fine-Tuning Architect and implement scalable solutions for training and fine-tuning LLMs Apply prompt engineering, transfer learning, and optimization techniques to enhance model performance. Integrate LLMs into customer-facing applications such as chatbots, VOICE AI agents, Expert AI agents, and recommendation engines. 2. Customer Experience (CX) Technology Integration Collaborate with CX and product teams to embed AI into customer journeys, improving personalization, automation, and engagement. Design AI-driven solutions for omnichannel support, sentiment analysis, and real-time feedback loops. Ensure AI systems align with customer satisfaction goals and ethical AI principles. 3. Technical Leadership & Team Management Lead and mentor a multidisciplinary team of AI engineers, data scientists, and MLOps professionals. Drive agile development practices and foster a culture of innovation and accountability. 4. Research & Innovation Conduct and apply research in NLP, LLMs, and AI infrastructure to solve real-world customer experience problems. Contribute to publications, patents, or open-source initiatives as appropriate. Guide team and maintain detailed architecture diagrams, design documents, and technical specifications. 5. Product Roadmap & Delivery Define and execute the AI product roadmap in collaboration with engineering and business stakeholders. Manage timelines, deliverables, and cross-functional dependencies. Plan and manage GPU infrastructure for training and inference (e.g., A100, H100, L40S). 6. Deployment & MLOps Deploy AI models on Azure, AWS , and on-premise GPU clusters using containerized and scalable architectures. Integrate with CI/CD pipelines and ensure robust monitoring, logging, and rollback mechanisms. Qualifications Master’s or Ph.D. in Computer Science, AI, Machine Learning, or related field. 5+ years of experience in AI/ML, with 1.5 + years in a leadership or GEN AI architect role. Proven experience with LLMs, Transformers, and fine-tuning frameworks (e.g., Hugging Face). Strong understanding of customer experience platforms and how AI can enhance them. Proficiency in Python, PyTorch, TensorFlow, and MLOps tools. Experience with cloud platforms (Azure, AWS) and on-premise GPU infrastructure. Why Join Us? Shape the future of AI-powered customer experiences, visibility to global customer AI deployments. Lead a high-impact team working on state-of-the-art technologies. Competitive compensation, and continuous learning opportunities Show more Show less

Job Title Senior Backend Developer (Laravel & PHP) Gadget Guruz is India’s pioneering on-site electronics repair and e-waste management platform based in Delhi NCR. We bridge the gap between independent technicians and customers via our Digital products (Website and Apps) and proprietary hardware solutions. Our mission is to bring quality, transparency and accountability to a largely unorganized industry. Role Overview As a Senior Backend Developer, you will be a full-time, on-site member of our Delhi NCR team, owning the design, implementation and maintenance of our core server-side systems. You’ll work in a fast-paced, growth-stage startup environment—with blurred lines between Dev, Ops and Product—to build scalable, secure and high-performance APIs that power both web and mobile clients. Key Responsibilities Architecture & Development Lead end-to-end Laravel application design and coding, following clean-code and OOP principles Build and version RESTful and GraphQL APIs for web (AJAX/Blade/Bootstrap) and mobile (Flutter) clients Database & Performance Model MySQL schemas, optimize queries and manage migrations Implement caching (Redis/Memcached), queueing (RabbitMQ/SQS) and conduct load-testing Cloud Infrastructure Deploy, monitor and scale services on AWS (EC2, RDS, S3, Lambda, CloudWatch) Define Infrastructure-as-Code with Terraform or CloudFormation AI/ML & Real-Time Features Integrate ML models via inference endpoints in collaboration with Data Science (Preferred) Build real-time chat or notification services using WebSockets/Socket.IO Quality & Security Enforce web-security best practices (OWASP, input validation, encryption) Own CI/CD pipelines (GitHub Actions/Jenkins), unit/integration tests (PHPUnit, Mockery) Collaboration & Mentorship Partner with Frontend (Vue/React/Bootstrap) and Mobile (Flutter) teams on API contracts Mentor junior engineers and drive code reviews, documentation and knowledge sharing Must Have Qualifications 5+ years of backend experience with Laravel and PHP (strong OOP & design-pattern skills) Bachelor’s degree in Computer Science, Software Engineering or a related field Deep expertise in MySQL design, optimisation and migrations Proven track record building and securing RESTful or GraphQL APIs Hands-on AWS experience (EC2, RDS, S3, Lambda) and IaC (Terraform/CloudFormation) Solid understanding of web security best practices (OWASP Top 10, HTTPS, CSRF/XSS mitigation) Experience with version control workflows (Git) and setting up CI/CD Demonstrated ability to thrive in a growth-stage startup environment Preferred Skills Real-time frameworks: Node.js/Express.js with Socket.IO or Pusher Containerization (Docker) and orchestration (Kubernetes) NoSQL databases (MongoDB, DynamoDB) Serverless architectures (AWS Lambda, API Gateway) AI/ML model deployment and inference pipelines What we offer Competitive salary + ESOPs Flexible on-site/remote hybrid model (Delhi HQ) Equity participation and a seat at the table in shaping India’s repair-tech revolution How to Apply Fill this form https://forms.gle/vdvwpRd7SeUtuWAp9 , Share GitHub/portfolio links and a one-paragraph cover letter on a project where you built a scalable backend to hr@gadgetguruz.com with Subject: Senior Backend Developer – Your Name We look forward to building the future of electronics repair—and making India greener—together! Show more Show less

Applied Machine Learning Scientist – Voice AI, NLP & GenAI Applications Location : Sector 63, Gurugram, Haryana – 100% In-Office Working Days : Monday to Friday, with 2nd and 4th Saturdays off Working Hours : 10:30 AM – 8:00 PM Experience : 3–7 years in applied ML, with at least 2 years focused on voice, NLP, or GenAI deployments Function : AI/ML Research & Engineering | Conversational Intelligence | Real-time Model Deployment Apply : careers@darwix.ai Subject Line : “Application – Applied ML Scientist – [Your Name]” About Darwix AI Darwix AI is a GenAI-powered platform transforming how enterprise sales, support, and credit teams engage with customers. Our proprietary AI stack ingests data across calls, chat, email, and CCTV streams to generate: Real-time nudges for agents and reps Conversational analytics and scoring to drive performance CCTV-based behavior insights to boost in-store conversion We’re live across leading enterprises in India and MENA, including IndiaMart, Wakefit, Emaar, GIVA, Bank Dofar , and others. We’re backed by top-tier operators and venture investors and scaling rapidly across multiple verticals and geographies. Role Overview We are looking for a hands-on, impact-driven Applied Machine Learning Scientist to build, optimize, and productionize AI models across ASR, NLP, and LLM-driven intelligence layers . This is a core role in our AI/ML team where you’ll be responsible for building the foundational ML capabilities that drive our real-time sales intelligence platform. You will work on large-scale multilingual voice-to-text pipelines, transformer-based intent detection, and retrieval-augmented generation systems used in live enterprise deployments. Key ResponsibilitiesVoice-to-Text (ASR) Engineering Deploy and fine-tune ASR models such as WhisperX, wav2vec 2.0, or DeepSpeech for Indian and GCC languages Integrate diarization and punctuation recovery pipelines Benchmark and improve transcription accuracy across noisy call environments Optimize ASR latency for real-time and batch processing modes NLP & Conversational Intelligence Train and deploy NLP models for sentence classification, intent tagging, sentiment, emotion, and behavioral scoring Build call scoring logic aligned to domain-specific taxonomies (sales pitch, empathy, CTA, etc.) Fine-tune transformers (BERT, RoBERTa, etc.) for multilingual performance Contribute to real-time inference APIs for NLP outputs in live dashboards GenAI & LLM Systems Design and test GenAI prompts for summarization, coaching, and feedback generation Integrate retrieval-augmented generation (RAG) using OpenAI, HuggingFace, or open-source LLMs Collaborate with product and engineering teams to deliver LLM-based features with measurable accuracy and latency metrics Implement prompt tuning, caching, and fallback strategies to ensure system reliability Experimentation & Deployment Own model lifecycle: data preparation, training, evaluation, deployment, monitoring Build reproducible training pipelines using MLflow, DVC, or similar tools Write efficient, well-structured, production-ready code for inference APIs Document experiments and share insights with cross-functional teams Required Qualifications Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or related fields 3–7 years experience applying ML in production, including NLP and/or speech Experience with transformer-based architectures for text or audio (e.g., BERT, Wav2Vec, Whisper) Strong Python skills with experience in PyTorch or TensorFlow Experience with REST APIs, model packaging (FastAPI, Flask, etc.), and containerization (Docker) Familiarity with audio pre-processing, signal enhancement, or feature extraction (MFCC, spectrograms) Knowledge of MLOps tools for experiment tracking, monitoring, and reproducibility Ability to work collaboratively in a fast-paced startup environment Preferred Skills Prior experience working with multilingual datasets (Hindi, Arabic, Tamil, etc.) Knowledge of diarization and speaker separation algorithms Experience with LLM APIs (OpenAI, Cohere, Mistral, LLaMA) and RAG pipelines Familiarity with inference optimization techniques (quantization, ONNX, TorchScript) Contribution to open-source ASR or NLP projects Working knowledge of AWS/GCP/Azure cloud platforms What Success Looks Like Transcription accuracy improvement ≥ 85% across core languages NLP pipelines used in ≥ 80% of Darwix AI’s daily analyzed calls 3–5 LLM-driven product features delivered in the first year Inference latency reduced by 30–50% through model and infra optimization AI features embedded across all Tier 1 customer accounts within 12 months Life at Darwix AI You will be working in a high-velocity product organization where AI is core to our value proposition. You’ll collaborate directly with the founding team and cross-functional leads, have access to enterprise datasets, and work on ML systems that impact large-scale, real-time operations. We value rigor, ownership, and speed. Model ideas become experiments in days, and successful experiments become deployed product features in weeks. Compensation & Perks Competitive fixed salary based on experience Quarterly/Annual performance-linked bonuses ESOP eligibility post 12 months Compute credits and model experimentation environment Health insurance, mental wellness stipend Premium tools and GPU access for model development Learning wallet for certifications, courses, and AI research access Career Path Year 1: Deliver production-grade ASR/NLP/LLM systems for high-usage product modules Year 2: Transition into Senior Applied Scientist or Tech Lead for conversation intelligence Year 3: Grow into Head of Applied AI or Architect-level roles across vertical product lines How to Apply Email the following to careers@darwix.ai : Updated resume (PDF) A short write-up (200 words max): “How would you design and optimize a multilingual voice-to-text and NLP pipeline for noisy call center data in Hindi and English?” Optional: GitHub or portfolio links demonstrating your work Subject Line : “Application – Applied Machine Learning Scientist – [Your Name]” Show more Show less

Job description 🚀 Job Title: ML Engineer Company : Darwix AI Location : Gurgaon (On-site) Type : Full-Time Experience : 2-6 Years Level : Senior Level 🌐 About Darwix AI Darwix AI is one of India’s fastest-growing GenAI startups, revolutionizing the future of enterprise sales and customer engagement with real-time conversational intelligence. We are building a GenAI-powered agent-assist and pitch intelligence suite that captures, analyzes, and enhances every customer interaction—across voice, video, and chat—in real time. We serve leading enterprise clients across India, the UAE, and Southeast Asia and are backed by global VCs, top operators from Google, Salesforce, and McKinsey, and CXOs from the industry. This is your opportunity to join a high-caliber founding tech team solving frontier problems in real-time voice AI, multilingual transcription, retrieval-augmented generation (RAG), and fine-tuned LLMs at scale. 🧠 Role Overview As the ML Engineer , you will drive the development, deployment, and optimization of AI systems that power Darwix AI's real-time conversation intelligence platform. This includes voice-to-text transcription, speaker diarization, GenAI summarization, prompt engineering, knowledge retrieval, and real-time nudge delivery. You will lead a team of AI engineers and work closely with product managers, software architects, and data teams to ensure technical excellence, scalable architecture, and rapid iteration cycles. This is a high-ownership, hands-on leadership role where you will code, architect, and lead simultaneously. 🔧 Key Responsibilities 1. AI Architecture & Model Development Architect end-to-end AI pipelines for transcription, real-time inference, LLM integration, and vector-based retrieval. Build, fine-tune, and deploy STT models (Whisper, Wav2Vec2.0) and diarization systems for speaker separation. Implement GenAI pipelines using OpenAI, Gemini, LLaMA, Mistral, and other LLM APIs or open-source models. 2. Real-Time Voice AI System Development Design low-latency pipelines for capturing and processing audio in real-time across multi-lingual environments. Work on WebSocket-based bi-directional audio streaming, chunked inference, and result caching. Develop asynchronous, event-driven architectures for voice processing and decision-making. 3. RAG & Knowledge Graph Pipelines Create retrieval-augmented generation (RAG) systems that pull from structured and unstructured knowledge bases. Build vector DB architectures (e.g., FAISS, Pinecone, Weaviate) and connect to LangChain/LlamaIndex workflows. Own chunking, indexing, and embedding strategies (OpenAI, Cohere, Hugging Face embeddings). 4. Fine-Tuning & Prompt Engineering Fine-tune LLMs and foundational models using RLHF, SFT, PEFT (e.g., LoRA) as needed. Optimize prompts for summarization, categorization, tone analysis, objection handling, etc. Perform few-shot and zero-shot evaluations for quality benchmarking. 5. Pipeline Optimization & MLOps Ensure high availability and robustness of AI pipelines using CI/CD tools, Docker, Kubernetes, and GitHub Actions. Work with data engineering to streamline data ingestion, labeling, augmentation, and evaluation. Build internal tools to benchmark latency, accuracy, and relevance for production-grade AI features. 6. Team Leadership & Cross-Functional Collaboration Lead, mentor, and grow a high-performing AI engineering team. Collaborate with backend, frontend, and product teams to build scalable production systems. Participate in architectural and design decisions across AI, backend, and data workflows. 🛠️ Key Technologies & Tools Languages & Frameworks : Python, FastAPI, Flask, LangChain, PyTorch, TensorFlow, HuggingFace Transformers Voice & Audio : Whisper, Wav2Vec2.0, DeepSpeech, pyannote.audio, AssemblyAI, Kaldi, Mozilla TTS Vector DBs & RAG : FAISS, Pinecone, Weaviate, ChromaDB, LlamaIndex, LangGraph LLMs & GenAI APIs : OpenAI GPT-4/3.5, Gemini, Claude, Mistral, Meta LLaMA 2/3 DevOps & Deployment : Docker, GitHub Actions, CI/CD, Redis, Kafka, Kubernetes, AWS (EC2, Lambda, S3) Databases : MongoDB, Postgres, MySQL, Pinecone, TimescaleDB Monitoring & Logging : Prometheus, Grafana, Sentry, Elastic Stack (ELK) 🎯 Requirements & Qualifications 👨‍💻 Experience 2-6 years of experience in building and deploying AI/ML systems, with at least 2+ years in NLP or voice technologies. Proven track record of production deployment of ASR, STT, NLP, or GenAI models. Hands-on experience building systems involving vector databases, real-time pipelines, or LLM integrations. 📚 Educational Background Bachelor's or Master's in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Tier 1 institute preferred (IITs, BITS, IIITs, NITs, or global top 100 universities). ⚙️ Technical Skills Strong coding experience in Python and familiarity with FastAPI/Django. Understanding of distributed architectures, memory management, and latency optimization. Familiarity with transformer-based model architectures, training techniques, and data pipeline design. 💡 Bonus Experience Worked on multilingual speech recognition and translation. Experience deploying AI models on edge devices or browsers. Built or contributed to open-source ML/NLP projects. Published papers or patents in voice, NLP, or deep learning domains. 🚀 What Success Looks Like in 6 Months Lead the deployment of a real-time STT + diarization system for at least 1 enterprise client. Deliver high-accuracy nudge generation pipeline using RAG and summarization models. Build an in-house knowledge indexing + vector DB framework integrated into the product. Mentor 2–3 AI engineers and own execution across multiple modules. Achieve <1 sec latency on real-time voice-to-nudge pipeline from capture to recommendation. 💼 What We Offer Compensation : Competitive fixed salary + equity + performance-based bonuses Impact : Ownership of key AI modules powering thousands of live enterprise conversations Learning : Access to high-compute GPUs, API credits, research tools, and conference sponsorships Culture : High-trust, outcome-first environment that celebrates execution and learning Mentorship : Work directly with founders, ex-Microsoft, IIT-IIM-BITS alums, and top AI engineers Scale : Opportunity to scale an AI product from 10 clients to 100+ globally within 12 months ⚠️ This Role is NOT for Everyone 🚫 If you're looking for a slow, abstract research role—this is NOT for you. 🚫 If you're used to months of ideation before shipping—you won't enjoy our speed. 🚫 If you're not comfortable being hands-on and diving into scrappy builds—you may struggle. ✅ But if you’re a builder , architect , and visionary —who loves solving hard technical problems and delivering real-time AI at scale, we want to talk to you. 📩 How to Apply Send your CV, GitHub/portfolio, and a brief note on “Why AI at Darwix?” to: 📧 careers@cur8.in / vishnu.sethi@cur8.in Subject Line: Application – ML Engineer – [Your Name] Include links to: Any relevant open-source contributions LLM/STT models you've fine-tuned or deployed RAG pipelines you've worked on 🔍 Final Thought This is not just a job. This is your opportunity to build the world’s most scalable AI sales intelligence platform —from India, for the world. Show more Show less

Head of AI & ML Platforms Focus : Voice AI, NLP, Conversation Intelligence for Omnichannel Enterprise Sales Location : Sector 63, Gurugram, Haryana — Full-time, 100% In-Office Work Hours : 10:30 AM – 8:00 PM, Monday to Friday (2nd and 4th Saturdays off) Experience Required : 8–15 years in AI/ML, with 3+ years leading teams in voice, NLP, or conversation platforms Apply : careers@darwix.ai Subject Line : “Application – Head of AI & ML Platforms – [Your Name]” About Darwix AI Darwix AI is a GenAI-powered platform for enterprise revenue teams across sales, support, credit, and retail. Our proprietary AI stack ingests multimodal inputs—voice calls, chat logs, emails, and CCTV streams—and delivers contextual nudges, conversation scoring, and performance analytics in real time. Our suite of products includes: Transform+ : Real-time conversational intelligence for contact centers and field sales Sherpa.ai : A multilingual GenAI assistant that provides in-the-moment coaching, summaries, and objection handling support Store Intel : A computer vision solution that transforms CCTV feeds into actionable insights for physical retail spaces Darwix AI is trusted by large enterprises such as IndiaMart, Wakefit, Emaar, GIVA, Bank Dofar, and Sobha Realty , and is backed by leading institutional and operator investors. We are expanding rapidly across India, the Middle East, and Southeast Asia. Role Overview We are seeking a highly experienced and technically strong Head of AI & ML Platforms to architect and lead the end-to-end AI systems powering our voice intelligence, NLP, and GenAI solutions. This is a leadership role that blends research depth with applied engineering execution. The ideal candidate will have deep experience in building and deploying voice-to-text pipelines, multilingual NLP systems, and production-grade inference workflows. The individual will be responsible for model design, accuracy benchmarking, latency optimization, infrastructure orchestration, and integration across our product suite. This is a critical leadership role with direct influence over product velocity, enterprise client outcomes, and future platform scalability. Key ResponsibilitiesVoice-to-Text (ASR) Architecture Lead the design and optimization of large-scale automatic speech recognition (ASR) pipelines using open-source and commercial frameworks (e.g., WhisperX, Deepgram, AWS Transcribe) Enhance speaker diarization, custom vocabulary accuracy, and latency performance for real-time streaming scenarios Build fallback ASR workflows for offline and batch mode processing Implement multilingual and domain-specific tuning, especially for Indian and GCC languages Natural Language Processing and Conversation Analysis Build NLP models for conversation segmentation, intent detection, tone/sentiment analysis, and call scoring Implement multilingual support (Hindi, Arabic, Tamil, etc.) with fallback strategies for mixed-language and dialectal inputs Develop robust algorithms for real-time classification of sales behaviors (e.g., probing, pitching, objection handling) Train and fine-tune transformer-based models (e.g., BERT, RoBERTa, DeBERTa) and sentence embedding models for text analytics GenAI and LLM Integration Design modular GenAI pipelines for nudging, summarization, and response generation using tools like LangChain, LlamaIndex, and OpenAI APIs Implement retrieval-augmented generation (RAG) architectures for contextual, accurate, and hallucination-resistant outputs Build prompt orchestration frameworks that support real-time sales coaching across channels Ensure safety, reliability, and performance of LLM-driven outputs across use cases Infrastructure and Deployment Lead the development of scalable, secure, and low-latency AI services deployed via FastAPI, TorchServe, or similar frameworks Oversee model versioning, monitoring, and retraining workflows using MLflow, DVC, or other MLOps tools Build hybrid inference systems for batch, real-time, and edge scenarios depending on product usage Optimize inference pipelines for GPU/CPU balance, resource scheduling, and runtime efficiency Team Leadership and Cross-functional Collaboration Recruit, manage, and mentor a team of machine learning engineers and research scientists Collaborate closely with Product, Engineering, and Customer Success to translate product requirements into AI features Own AI roadmap planning, sprint delivery, and KPI measurement Serve as the subject-matter expert for AI-related client discussions, sales demos, and enterprise implementation roadmaps Required Qualifications 8+ years of experience in AI/ML with a minimum of 3 years in voice AI, NLP, or conversational platforms Proven experience delivering production-grade ASR or NLP systems at scale Deep familiarity with Python, PyTorch, HuggingFace, FastAPI, and containerized environments (Docker/Kubernetes) Expertise in fine-tuning LLMs and building multi-language, multi-modal intelligence stacks Demonstrated experience with tools such as WhisperX, Deepgram, Azure Speech, LangChain, MLflow, or Triton Inference Server Experience deploying real-time or near real-time inference models at enterprise scale Strong architectural thinking with the ability to design modular, reusable, and scalable ML services Track record of building and leading high-performing ML teams Preferred Skills Background in telecom, contact center AI, conversational analytics, or field sales optimization Familiarity with GPU deployment, model quantization, and inference optimization Experience with low-resource languages and multilingual data augmentation Understanding of sales enablement workflows and domain-specific ontology development Experience integrating AI models into customer-facing SaaS dashboards and APIs Success Metrics Transcription accuracy improvement by ≥15% across core languages within 6 months End-to-end voice-to-nudge latency reduced below 5 seconds GenAI assistant adoption across 70%+ of eligible conversations AI-driven call scoring rolled out across 100% of Tier 1 clients within 9 months Model deployment velocity (dev to prod) reduced by ≥40% through tooling and process improvements Culture at Darwix AI At Darwix AI, we operate at the intersection of engineering velocity and product clarity. We move fast, prioritize outcomes over optics, and expect leaders to drive hands-on impact. You will work directly with the founding team and senior leaders across engineering, product, and GTM functions. Expect ownership, direct communication, and a culture that values builders who scale systems, people, and strategy. Compensation and Benefits Competitive fixed compensation Performance-based bonuses and growth-linked incentives ESOP eligibility for leadership candidates Access to GPU/compute credits and model experimentation infrastructure Comprehensive medical insurance and wellness programs Dedicated learning and development budget for technical and leadership upskilling MacBook Pro, premium workstation, and access to industry tooling licenses Career Progression 12-month roadmap: Build and stabilize AI platform across all product lines 18–24-month horizon: Elevate to VP of AI or Chief AI Officer as platform scale increases globally Future leadership role in enabling new verticals (e.g., healthcare, finance, logistics) with domain-specific GenAI solutions How to Apply Send the following to careers@darwix.ai : Updated CV (PDF format) A short statement (200 words max) on: “How would you design a multilingual voice-to-text pipeline optimized for low-resource Indic languages, with real-time nudge delivery?” Links to any relevant GitHub repos, publications, or deployed projects (optional) Subject Line : “Application – Head of AI & ML Platforms – [Your Name]” Show more Show less

The Host Networking team is responsible for millions of NICs in the fleet that powers all of Meta’s services and applications as well as the transport software for Meta’s Training and Inference Accelerators. This Software Engineer will be working on NICs and Transport solution addressing growing demands of the distributed fleet of accelerators for our AI workloads. Do you want to work on transport for large scale AI clusters? Do you want to develop innovative solutions to our challenges and ship them into production? This role on our host networking teams is for you! Software Engineer - Host Networking Responsibilities: Design and implement drivers (and/or Firmware) for (network) ethernet adapter functions, Transport stack for RDMA, control functions with the host/accelerators. Build tests and help build an integrated CI/CD pipeline for delivery of software Bringup the stack in simulation and emulation environments Hardware bringup and test in a scaled environment Minimum Qualifications: Proficient in programming in C/C++/Python Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Experience with Linux Kernel, especially drivers and network stack Working knowledge of transport stack particularly RDMA (RoCEv2) Hands on experience with debugging large scale systems Successful candidate must remain in role in the same team in India for a minimum period of 24 months before being eligible for transfer to another role, team or location. Preferred Qualifications: Experience with Qemu, FPGA Emulation environment is a plus About Meta: Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics. Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta. Show more Show less

Job Description Job Title : AI Engineer Location : Mohali (Onsite) Shift : UK Shift (12 PM to 10 PM) Experience : 1 to 2 years Qualifications Bachelor's degree in Computer Science, Business, or a related field. Specialization or certification in AI/ML is a plus. Job Role & Responsibilities Develop and optimize predictive models for AI and ML-based features, focusing on enhancing accuracy and latency. Write clean, efficient, reusable, testable, and scalable code with a focus on best coding practices. Analyze business requirements, translate them into software components, and implement feature modifications. Design and implement high-availability, low-latency applications with data protection and security features. Profile applications to ensure optimal performance and identify potential bottlenecks. Continuously work on optimizing NLP-based models, improving both their accuracy and latency for real-world applications. Write unit test cases to ensure code quality and reliability, using appropriate testing frameworks. Continuously optimize and refactor code for improved performance, scalability, and maintainability. Skills & Expertise Strong expertise in building solutions using AI/ML/DL open-source libraries. Advanced Python programming skills. Strong problem-solving and analytical abilities. Ability to write optimized, well-documented code following best coding practices. Proficient in optimizing models for both accuracy and latency, particularly in NLP and machine learning applications. Proficient in optimizing NLP-based models, including techniques for faster inference and reduced computational cost. Familiarity with Generative AI, Large Language Models (LLM), Embeddings, Vectors, RAG (Retrieval-Augmented Generation), and Prompting. Tools & Technologies AI/ML Libraries: TensorFlow, PyTorch, Flair, BERT, DeBERTa, and other latest libraries for text analytics. Frameworks & Platforms: Streamlit, FastAPI. Specialized Tools: Ollama, Vector Databases. Profiling & Testing: Familiarity with tools for profiling applications (e.g., cProfile, Py-Spy) and writing unit tests (e.g., PyTest, UnitTest). Optimization Techniques: Techniques such as model quantization, pruning, distillation, and hardware acceleration. Technical Expertise Minimum of 1 year of hands-on experience in AI/ML/DL projects, focusing on Natural Language Processing (NLP), Named Entity Recognition (NER), and Text Analytics. Strong understanding and practical experience with deep learning techniques, including recommendation engines and advanced AI solutions. Proven experience in optimizing NLP models for accuracy and latency in production environments. Experience with Retrieval-Augmented Generation (RAG) application development and generative AI. Familiarity with Agent Prompting and its applications. Experience in AI applications within the HR domain is highly preferred. Knowledge of Reinforcement Learning is a plus. Certifications or specialization in Artificial Intelligence is highly desirable. Show more Show less

Role Type: Solution Author Employment Type: Contract-Based Location: Remote Shift Timing: Early Morning Shift – 4:00 AM to 12:00 PM IST (8 hours) Note: Fresh graduates with strong subject knowledge are encouraged to apply. Overview: Endeavor Academy, a leading EdTech service provider dedicated to academic excellence, is hiring a Subject Matter Expert (SME) in Statistics and Probability for an 8-hour early morning shift. As a Solution Author, you will be responsible for creating accurate, step-by-step academic content, resolving student queries, and contributing to assessments through our interactive online platform. Key Responsibilities: Solution Authoring Prepare clear, concise, and comprehensive step-by-step solutions across topics such as: Descriptive Statistics (Mean, Median, Mode, Variance, Standard Deviation) Probability Theory (Basic Probability, Conditional Probability, Bayes’ Theorem) Probability Distributions (Normal, Binomial, Poisson, Exponential) Hypothesis Testing (t-tests, Chi-square, ANOVA) Regression Analysis (Simple and Multiple Regression) Statistical Inference (Confidence Intervals, p-values) Data Analysis and Interpretation Ensure content quality and alignment with academic standards. Student Doubt Resolution Address and resolve student questions and doubts through the online platform during shift hours. Deliver clear and easy-to-understand responses that promote concept clarity. Assessment Creation and Review Develop and validate academic questions and answer sets. Review student answers and offer constructive feedback. Content Accuracy and Quality Maintenance Ensure accuracy and completeness in all authored content. Regularly update solutions as per revised curriculum or feedback from reviewers. Qualifications: Bachelor’s or Master’s degree in Statistics, Mathematics, Data Science, or a related field Proficiency in core statistical and probability concepts Excellent written English communication Prior teaching, tutoring, or content development experience is a plus Skills and Attributes: Strong analytical and problem-solving abilities Attention to detail and commitment to academic integrity Good time management and ability to meet deadlines Enthusiasm for helping students learn complex concepts Why Join Endeavor Academy? Attractive compensation based on quality and volume Remote work with a stable 8-hour early morning shift Opportunity to make a meaningful impact on student learning Be part of a mission-driven, growing EdTech organization Application Process: Interested candidates should email their resume and any sample solutions (if available) to: 📧 hr@endeavoracademy.co.in Shortlisted applicants may be required to complete a brief subject assessment. Show more Show less