23 Model Optimization Jobs

As an AI Computer Vision Engineer with 4+ years of experience, you will be responsible for developing and training computer vision models for various tasks such as object detection, image classification, and face recognition. You will optimize models for performance on edge devices and apply data augmentation techniques to image/video datasets. Additionally, you will need proficiency in Large Language Models and a strong understanding of statistical analysis and machine learning algorithms. Your role will involve hands-on implementation of machine learning algorithms like linear regression, logistic regression, decision trees, and clustering algorithms. Understanding image processing concepts and experience in model optimization, quantization, or deploying to edge devices will be essential. You should have strong programming skills in Python (or C++) and expertise in implementing and optimizing machine learning pipelines for seamless integration into production systems. Experience with real-time computer vision applications, OpenCV, NumPy, PyTorch/TensorFlow, and computer vision models like YOLOv5, Mask R-CNN will be beneficial. Engaging with multiple teams, contributing to key decisions, and providing solutions that apply across multiple teams are expected from you. You will lead the implementation of large language models in AI applications and research cutting-edge AI techniques to enhance system performance. Contribution to the development and deployment of AI solutions across various domains is also part of your responsibilities. In terms of requirements, you should design, develop, and deploy ML models for OCR-based text extraction, table and line-item detection, and named entity recognition. Evaluating and integrating third-party OCR tools, developing pre-processing and post-processing pipelines for image/text data, and familiarity with video analytics platforms are necessary skills. Experience with MLOps tools, academic CV research, and knowledge of GPU acceleration or hardware integration will be advantageous for this role.,

Company Size Large-scale / Global Experience Required 3 - 5 years Working Days 6 days/week Office Location Viman Nagar, Pune Role & Responsibilities Agentic AI Development: Design and develop multi-agent conversational frameworks with adaptive decision-making capabilities. Integrate goal-oriented reasoning and memory components into agents using transformer-based architectures. Build negotiation-capable bots with real-time context adaptation and recursive feedback processing. Generative AI & Model Optimization: Fine-t une LLMs/SLMs using proprietary and domain-specific datasets (NBFC, Financial Services, etc.). Apply distillation and quantization for efficient deployment on edge devices. Benchmark LLM/SLM performance on server vs. edge environments for real-time use cases. Speech And Conversational Intelligence: Implement contextual dialogue flows using speech inputs with emotion and intent tracking. Evaluate and deploy advanced Speech-to-Speech (S2S) models for naturalistic voice responses. Work on real-time speaker diarization and multi-turn, multi-party conversation tracking. Voice Biometrics & AI Security: Train and evaluate voice biometric models for secure identity verification. Implement anti-spoofing layers to detect deepfakes, replay attacks, and signal tampering. Ensure compliance with voice data privacy and ethical AI guidelines. Self-Learning & Autonomous Adaptation: Develop frameworks for agents to self-correct and adapt using feedback loops without full retraining. Enable low-footprint learning systems on-device to support personalization on the edge. Ideal Candidate Educational Qualifications: Bachelors/Masters degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field. Experience Required: 35 years of experience, with a mix of core software development and AI/ML model engineering. Proven hands-on work with Conversational AI, Generative AI, or Multi-Agent Systems. Technical Proficiency: Strong programming in Python, TensorFlow/PyTorch, and model APIs (Hugging Face, LangChain, OpenAI, etc.). Expertise in STT, TTS, S2S, speaker diarization, and speech emotion recognition. LLM fine-tuning, model optimization (quantization, distillation), RAG pipelines. Understanding of agentic frameworks, cognitive architectures, or belief-desire-intention (BDI) models. Familiarity with Edge AI deployment, low-latency model serving, and privacy-compliant data pipelines. Desirable: Exposure to agent-based simulation, reinforcement learning, or behavioralmodeling. Publications, patents, or open-source contributions in conversational AI or GenAI systems. Perks, Benefits and Work Culture Our people define our passion and our audacious, incredibly rewarding achievements. Bajaj Finance Limited is one of Indias most diversified Non-banking financial companies, and among Asias top 10 Large workplaces. If you have the drive to get ahead, we can help find you an opportunity at any of the 500+ locations were present in India. Skills: edge ai deployment,adaptation,speech emotion recognition,llm fine-tuning,tensorflow,models,intelligence,model optimization,speech,speech-to-speech,data,openai,hugging face,llm,optimization,agents,langchain,pytorch,python Show more Show less

You will be joining our team as a skilled Deep Learning Engineer with expertise in object detection and segmentation models. Your primary responsibilities will include implementing and refining object detection models such as YOLOvX, Faster R-CNN, EfficientDet, SSD, and Mask R-CNN. Additionally, you will work on real-time computer vision applications, optimize performance, annotate and prepare datasets, and collaborate on research and development projects to enhance model performance and robustness. As a Deep Learning Engineer, you will be expected to deploy models using Docker on Linux/Windows systems, with experience in edge deployment considered a plus. It will be essential for you to document code, experiments, and deployment processes while collaborating with cross-functional teams. Strong Python programming skills, knowledge of TensorFlow, PyTorch, OpenCV, and ONNX, as well as hands-on experience with Docker and familiarity with model optimization techniques like quantization and pruning are required for this role. An advantage would be your experience in edge deployments using platforms such as NVIDIA Jetson, TensorRT, and OpenVINO. Additionally, familiarity with experiment tracking tools like MLflow or Weights & Biases is a plus. The qualifications we are looking for include a Bachelors or Masters degree in Computer Science, AI, Data Science, or a related field, along with strong analytical, problem-solving, and team collaboration skills. This is a full-time position with a day shift schedule that requires in-person work at our location.,

As a Research Associate in Machine Learning / Deep Learning at our location in Kollam, Kerala, you will be responsible for conducting original research in the field of machine learning (ML) and/or deep learning (DL) to meet the project objectives. Your role will involve designing, developing, and optimizing ML/DL algorithms and models specifically for time series analysis of skilled and unskilled movement patterns captured using smart gloves. Collaboration with interdisciplinary teams of researchers to contribute to publications, reports, and technical documentation will be a key aspect of your work. Additionally, you will assist the Principal Investigator (PI) in research dissemination and ensuring compliance with funding-related requirements. To excel in this role, you should possess a B-Tech qualification and have a passion for research in machine learning and deep learning. The deadline to apply for this position is July 26, 2025.,

About Guidesly: Do you enjoy the Outdoors? Are you an enthusiast who wants to work in a place where you can follow your personal and professional passions? Guidesly is a well-funded startup building software for the Outdoor industry. Mobile apps, SaaS software, product services, and websites; we have a bit of everything. Sophisticated technology and a dream to change the world. If your passion is the outdoors and you want to live your dream, then this is your job. Work with guides, build products, get honest feedback from enthusiasts to create the very best solutions in the marketplace. The outdoor recreation industry includes fishing, wildlife, boating, water sports, snow sports, hunting, ATV, hiking, and biking. We are starting with the fishing vertical in the outdoor recreation industry. The product manager will work with professional guides throughout the United States and enthusiasts in all fishing varieties. Key Responsibilities: Develop and deploy machine learning, deep learning and NLP models for AI applications. Process and analyze large datasets, including feature extraction, vectorization, and embedding-based retrieval. Build and maintain backend systems and APIs to support AI-powered applications. Implement scalable AI solutions in cloud environments, primarily AWS. Develop end-to-end pipelines for model training, testing, and deployment using AWS services such as SageMaker, Bedrock, Lambda, and Step Functions. Optimize AI models for efficiency, scalability, and low-latency inference. Implement MLOps best practices for continuous integration, deployment, and monitoring of AI models. Document system architecture, API specifications, and performance benchmarks. Stay up to date with advancements in AI, including LLMs, FAISS, and deep learning frameworks, to drive innovation. Required Skills & Qualifications: Hands-on experience in AI/ML development, with expertise in natural language processing (NLP) and/or computer vision. Proficiency in Python, SQL, and machine learning libraries such as TensorFlow, PyTorch, and Scikit-learn. Strong understanding of LLM architectures, embeddings, and transformer-based models. Hands-on experience processing large datasets, including feature engineering, embedding retrieval, and vectorization. Experience with Cloud Services (Preferably AWS) for model deployment, data processing, and cloud-based AI solutions. Strong grasp of MLOps principles, including CI/CD pipelines, model monitoring, and workflow automation. Strong analytical and problem-solving skills with a proactive approach to AI model optimization. Excellent communication and teamwork skills to collaborate effectively with engineers, data scientists, and stakeholders. Key Technologies & Tools: Languages & Frameworks: Python, SQL, TensorFlow, PyTorch, Hugging Face Data Processing & Feature Engineering: Vectorization, Embeddings, FAISS Cloud & AI Services: AWS SageMakerAI, Bedrock, Lambda, Step Functions, Inference MLOps & Model Deployment: CI/CD, Model Optimization, API Integration Workflow Automation & AI Infrastructure Key skills: Machine Learning, Deep Learning, Python, SQL, TensorFlow, PyTorch, Hugging Face, AWS SageMakerAI, Lambda, Model Optimization, API Integration, AI Infrastructure

Role Details: Position: AI Lead Location: Hyderabad, Telangana, India Key Responsibilities: Spearhead the end-to-end development, deployment, and continuous optimization of cutting-edge AI/ML systemsGenerative AI, LLMs/MLLMs, RAG, autonomous agents, and custom MCP servers in production Architect and implement scalable Retrieval-Augmented Generation pipelines, multi-modal transformer systems, and autonomous multi-agent frameworks (LangChain, AutoGPT, BabyAGI, NVIDIA NeMo Agents) Lead deep-learning model design and delivery: ANN, CNN, RNN, LSTM/BiLSTM, attention-based Transformers (BERT, GPT, T5, Vision Transformers), GANs, VAEs, Diffusion models, and Mixture-of-Experts architectures Define and enforce best practices for prompt engineering, fine-tuning (LlamaIndex, Hugging Face), quantization (INT4, GGUF), pruning, distillation, and advanced inference optimizations Build and maintain robust MLOps pipelines: CI/CD (Git, Bitbucket, automated tests), model versioning (MLflow, Hugging Face Hub & LFS), Docker/GPU containerization, Kubernetes/OpenShift orchestration, Terraform infrastructure as code Design high-performance data engineering workflows: ETL optimization (Pandas, NumPy, Spark), real-time streaming (Kafka, RabbitMQ), and caching strategies (Redis) Ensure secure, compliant AI deployments by embedding Responsible AI principles (bias mitigation, transparency, privacy), governance frameworks, and regulatory controls. Monitor emerging research (self-supervised pre-training, federated learning, synthetic data, LLMOps) and integrate top innovations into production Collaborate closely with Product, DevOps, Data Engineering, and Security teams; mentor and guide engineers and data scientists in software engineering and model validation best practices Required Qualifications: Education: Masters or PhD in AI/ML, Computer Science (AI/ML specialization), Data Science, Mathematics, or related field Industry Experience: 15+ years in AI/ML roles, including 710 years hands-on in Generative AI and Deep Learning, plus 5+ years in senior or leadership positions Hands-On Coding & Deployment: Expert at architecting, writing, debugging, deploying, and optimizing production-grade AI/ML code in Python (primary), C++, R, Java/Spring Boot, with strong testing, code-review, and performance-profiling discipline Deep Learning & Generative AI Frameworks: Advanced usage of PyTorch, TensorFlow, ONNX, GGUF, Hugging Face Transformers & Diffusers; fine-tuning pipelines (LlamaIndex, custom scripts) Large Language & Multimodal Models: Production deployment of LLMs, Multimodal LLMs (vision-language models, cross-modal understanding), RAG systems, and custom MCP A2A servers; embedding management & vector search with Pinecone, Milvus, Chroma, Quadrant Advanced Model Optimization: Quantization, pruning, distillation, MoE routing, efficient inference strategies, prompt-engineering platforms (LangSmith, PromptFlow) Classical & Advanced ML: Proficiency in regression, decision trees, random forests, SVM; boosting (XGBoost, CatBoost, LightGBM); clustering (K-Means, DBSCAN, hierarchical); RL (Q-Learning, DDPG, PPO); statistical methods and optimization math Computer Vision & Document Processing: Expertise in OpenCV, PyMuPDF, python-docx/pptx, pytesseract for advanced text/image extraction and analysis Cloud & Infrastructure: GPU acceleration (CUDA, cuDNN); AWS (Bedrock, SageMaker), Azure AI Studio & GPU Containers, GCP (Vertex AI, Cloud Run), serverless AI, NVIDIA Triton Inference Server Backend & APIs: FastAPI, OpenAPI, Django REST Framework, Flask for building and scaling AI microservices Data Engineering & Storage: ETL pipelines, streaming, caching; relational (MySQL, Oracle SQL), NoSQL (MongoDB), vector DBs MLOps & Observability: MLflow, Kubeflow; Docker, Kubernetes, OpenShift; CI/CD (Git, Bitbucket); monitoring with Prometheus, Grafana, OpenTelemetry, Logstash, Kibana Security & Compliance: Secure coding, network security, and adherence to GDPR, HIPAA, GxP standards Industry Certifications & Research: Must hold at least one recognized AI/ML certification (e.g. AWS Certified Machine Learning – Specialty, Google Professional Machine Learning Engineer, Microsoft Certified: Azure AI Engineer Associate) and have published research papers in top-tier AI/ML conferences or journals (NeurIPS, ACM, arXiv, AAAI, JMLR). Good to Have Skills: PhD-level publications and advanced certifications (Stanford AI, MIT, AWS, Google) Experience with federated learning, synthetic data generation, privacy-preserving ML (differential privacy, homomorphic encryption), and edge/in-device inference (TensorFlow Lite, CoreML) Familiarity with Responsible AI toolkits, model cards/DataCard’s, and AI risk management frameworks Significant open-source contributions to major AI/ML projects Proven success integrating AI in regulated industries (Texting/Messaging, pharma, healthcare, finance) Industries and disciplines. How to Apply: If you are a passionate developer who loves coding and thrives in an innovative startup environment, apply now to join our journey in revolutionizing communication! Apply here or email to join@beetexting.com

Minimum qualifications: Bachelor's degree or equivalent practical experience. 2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree. 2 years of experience with data structures or algorithms. 1 year of experience with core GenAI concepts (LLM, Multi-Modal, Large Vision Models) and experience with text, image, video, or audio generation. 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging). Preferred qualifications: Master's degree or PhD in Computer Science or related technical fields. Experience developing accessible technologies. Responsibilities Write product or system development code. Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency,) Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback. Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality. Implement GenAI solutions, utilize ML infrastructure, and contribute to data preparation, optimization, and performance enhancements.

As a Computer Vision Engineer/Sr. Engineer specializing in Intelligent Video Analytics (IVA/AI) at our company in Vadodara, Gujarat, you will play a crucial role in the Software Development team focusing on IVA/Computer Vision. With a minimum of 2 years of experience and a degree in B.E/B.tech/M.E/ M.tech in EC, Electronics, Electronics & Telecommunication, Computer Engineering, CSE, or related fields, you will have the opportunity to work on cutting-edge projects that leverage deep learning and computer vision techniques to extract meaningful insights from video streams. Your day-to-day responsibilities will involve collaborating with cross-functional teams to design and implement algorithms using C/C++, OpenCV, and TensorFlow. You will lead and mentor a team of engineers, participate in design reviews, integrate video analytics solutions with existing systems, and execute AI algorithms using various platform-specific frameworks like TensorRT and TensorFlow Lite. Additionally, you will research new technologies and methodologies to enhance video analytics capabilities and document your work through code documentation and technical reports. The ideal candidate for this role will have a strong foundation in Deep Learning/Computer Vision projects, with expertise in neural networks, CNN, model training strategies, and deep learning frameworks such as Tensorflow, PyTorch, or Keras. Good programming skills in Python and C++, along with experience in projects like Object Detection, Motion Detection, and Face Recognition, will be beneficial. You should also possess the ability to optimize deep learning models for embedded form factors and have a thirst for continuous learning and advancement in the field. Joining our team will provide you with the opportunity to work for an Indian Tech Company that creates innovative products for a global audience. You will be part of a challenging and rewarding environment, receive a competitive salary and other benefits, and enjoy a generous leave schedule, including company-paid medical insurance for the whole family. If you are an innovative and tech-savvy individual looking to make a significant impact in the field of computer vision and AI, we encourage you to apply and be part of our dynamic team.,

As a Generative AI & LLM expert, you will be responsible for supporting the AI and ML team in designing, developing, fine-tuning, and deploying large language models and generative AI applications. This role offers a unique opportunity to work with state-of-the-art AI technologies and enhance your skills in machine learning, natural language processing, and deep learning. Your primary responsibilities will include architecting robust systems to integrate LLMs and support retrieval workflows, providing guidance on the use of Vector DBs and model deployment on cloud platforms, optimizing the fine-tuning process for business-specific LLM use cases, and designing applications with on-premise/cloud-based LLM, RAG, Langchain. Key skills required for this role include model training & fine-tuning, data preparation & preprocessing, prompt engineering, model evaluation & optimization, collaborating with cross-functional teams, documentation & reporting, managing and training LLM models, and generating embeddings and managing semantic search via Vector DBs. To qualify for this position, you should have completed a Bachelors or Masters degree in Computer Science, Data Science, Artificial Intelligence, or a related field. Additionally, you should have at least 7+ years of experience in building ML pipelines, feature engineering, or deploying models/LLMs on cloud platforms. Other skills considered include experience with machine learning pipelines, model optimization, feature engineering, proficiency in database indexing, familiarity with deploying ML models in cloud environments, leadership skills, and strategic thinking. If you are passionate about working with cutting-edge AI technologies and have a strong background in machine learning and deep learning, we encourage you to apply for this role in our Product Engineering category. You can submit your application by filling in your name, email, phone number, and attaching your resume. We look forward to potentially welcoming you to our team and collaborating on innovative AI projects.,

As an AI/ML Engineer at Left Right Mind, you will be part of our dynamic team working on cutting-edge GenAI solutions and deploying large language models (LLMs) for real-world applications. Your primary responsibilities will include developing and deploying AI/ML models to address business challenges, optimizing LLMs for specific domains, and building end-to-end ML pipelines encompassing data preprocessing, training, and evaluation. Additionally, you will work with both structured and unstructured data to extract valuable insights and collaborate closely with engineers to bring models into production effectively. We expect you to stay abreast of the latest advancements in GenAI, RAG, and LLM research, leveraging tools such as LangGraph, Autogen, TensorFlow, and PyTorch. Experience with deploying solutions on cloud platforms like AWS, Azure, or GCP using Docker/Kubernetes will be beneficial. The ideal candidate should possess a minimum of 4 years of experience in AI/ML, demonstrate proficiency in Python programming and ML frameworks, and have hands-on experience with LLMs like OpenAI GPT, Gemini, or Claude. Moreover, familiarity with NLP, feature engineering, and model optimization, along with strong problem-solving and teamwork skills, are highly valued traits in this role. At Left Right Mind, we foster a culture of exploration, inquiry, and innovation. Our work is purpose-driven and fueled by curiosity. If you are passionate about pushing the boundaries of AI/ML and eager to contribute to impactful projects, we encourage you to apply by filling out the form: [Application Form](https://lnkd.in/dtdBVTHE). For any inquiries or additional information, feel free to contact varad.deshpande@leftrightmind.com.,

We are hiring experienced AI Engineers for a full-time, 6-month on-premise role in Bengaluru (Electronic City) The role involves working on AI/ML solutions with open-source LLMs such as LLaMA, DeepSeek, and Mistral Strong Python programming skills, including data structures and algorithmic problem-solving, are essential Candidates must be comfortable deploying models on-premise and solving system-level challenges in Python Fine-tuning of LLMs, performance optimization, and working in Linux environments are desirable The role is hands-on and requires excellent analytical thinking and full-time office presence

The candidate for this role should have a strong background in machine learning algorithms, deep learning frameworks, and practical experience in building and deploying AI solutions. You will collaborate with cross-functional teams to design, develop, and implement innovative AI-driven products and solutions. Your responsibilities will include designing, developing, and deploying machine learning and deep learning models for various business applications. Leading and contributing to projects involving Generative AI, collaborating with data scientists, software engineers, and product managers to deliver end-to-end AI solutions, analyzing and preprocessing large datasets, developing predictive models and algorithms, evaluating and optimizing model performance, and staying up to date with the latest advancements in AI/ML and Generative AI research and technologies. You should be a self-directed and proactive professional who takes initiative, adapts quickly to new technologies and changing requirements, and strategically applies knowledge to solve complex business problems. It is essential to stay current with emerging AI trends, drive innovation, maintain a focus on code quality and best practices. To qualify for this role, you will need a Bachelor's degree in computer science, Data Science, Statistics, or a related field. 3-4 years of experience in AI/ML project development with a minimum of 2 years of hands-on experience with Generative AI is required. Proficiency in programming languages such as Python, experience with data manipulation libraries, and a solid grasp of machine learning techniques and algorithms are essential. Hands-on experience with various AI technologies and frameworks, as well as experience developing and deploying ML models via REST APIs, is also necessary. Preferred qualifications include relevant certifications in data science from reputed universities specializing in AI, strong analytical and problem-solving skills, effective verbal and written communication skills, and good presentation skills. At Emerson, a workplace where every employee is valued, respected, and empowered to grow is prioritized. The company fosters an environment that encourages innovation, collaboration, and diverse perspectives. Career development, inclusive culture, competitive benefits plans, flexible time off options, and employee wellbeing are key priorities at Emerson. Emerson is a global leader in automation technology and software, helping customers in critical industries operate more sustainably while improving productivity, energy security, and reliability. The company celebrates diversity, embraces challenges, and offers opportunities for professionals at all stages of their careers to make a difference.,

Key Skills: Machine Learning, Data Engineering, Python, TensorFlow, PyTorch, Statistical Analysis, Cloud Platforms (AWS/GCP/Azure), Data Structures, Big Data, ML Frameworks, Model Optimization, Predictive Modeling. Key Responsibilities: Develop and implement data-driven ML predictive models to advance intelligent automation and reporting. Assess, analyze, and organize large datasets to extract meaningful insights. Execute tests to validate machine learning models and algorithms. Optimize machine learning models for improved performance and accuracy. Collaborate with cross-functional teams to integrate machine learning solutions into existing systems. Monitor and maintain machine learning models to ensure ongoing accuracy and efficiency. Research and stay updated on the latest advancements in machine learning and ML techniques and applications. Document processes, methodologies, and model performance for transparency and reproducibility. Troubleshoot and resolve issues related to machine learning model deployment and operation. Mentor and provide technical guidance to junior engineers, sharing best practices and fostering a culture of continuous learning. Experience Requirement: 6-13 years of experience in machine learning, data engineering, or software development. Strong programming skills and proficiency in languages commonly used for ML and related tasks. Big Data skills and proficiency in data structures, modeling, and visualization. Proven background in statistical analysis and data analysis to support model training and evaluation. Excellent communication skills for working with stakeholders and translating technical concepts. Proficiency in Python and ML frameworks (TensorFlow, PyTorch, scikit-learn); experience with production-quality code. Strong background in statistics, mathematics, and data science. Experience with cloud platforms (AWS, GCP, Azure) and deploying ML models at scale is a plus. Education: Any Post Graduation, Any Graduation.

The ideal candidate for this position in Ahmedabad should be a graduate with at least 3 years of experience. At Bytes Technolab, we strive to create a cutting-edge workplace infrastructure that empowers our employees and clients. Our focus on utilizing the latest technologies enables our development team to deliver high-quality software solutions for a variety of businesses. You will be responsible for leveraging your 3+ years of experience in Machine Learning and Artificial Intelligence to contribute to our projects. Proficiency in Python programming and relevant libraries such as NumPy, Pandas, and scikit-learn is essential. Hands-on experience with frameworks like PyTorch, TensorFlow, Keras, Facenet, and OpenCV will be key in your role. Your role will involve working with GPU acceleration for deep learning model development using CUDA, cuDNN. A strong understanding of neural networks, computer vision, and other AI technologies will be crucial. Experience with Large Language Models (LLMs) like GPT, BERT, LLaMA, and familiarity with frameworks such as LangChain, AutoGPT, and BabyAGI are preferred. You should be able to translate business requirements into ML/AI solutions and deploy models on cloud platforms like AWS SageMaker, Azure ML, and Google AI Platform. Proficiency in ETL pipelines, data preprocessing, and feature engineering is required, along with experience in MLOps tools like MLflow, Kubeflow, or TensorFlow Extended (TFX). Expertise in optimizing ML/AI models for performance and scalability across different hardware architectures is necessary. Knowledge of Natural Language Processing (NLP), Reinforcement Learning, and data versioning tools like DVC or Delta Lake is a plus. Skills in containerization tools like Docker and orchestration tools like Kubernetes will be beneficial for scalable deployments. You should have experience in model evaluation, A/B testing, and establishing continuous training pipelines. Working in Agile/Scrum environments with cross-functional teams, understanding ethical AI principles, model fairness, and bias mitigation techniques are important. Familiarity with CI/CD pipelines for machine learning workflows and the ability to communicate complex concepts to technical and non-technical stakeholders will be valuable.,

You are an experienced Lead Generative AI Engineer responsible for training, optimizing, scaling, and deploying various generative AI models including large language models, voice/speech foundation models, vision, and multi-modal foundation models using cutting-edge techniques and frameworks. Your role involves architecting and implementing state-of-the-art neural architecture, robust training, and inference infrastructure to efficiently take complex models with billions of parameters to production while optimizing for low latency, high throughput, and cost efficiency. Your key responsibilities include: - Architecting and refining foundation model infrastructure to support optimized AI models deployment focusing on C/C++, CUDA, and kernel-level programming enhancements. - Implementing optimization techniques like quantization, distillation, sparsity, streaming, and caching for model performance enhancements. - Spearheading the development of Vision pipelines to ensure scalable training and inference workflows of billions of parameter foundation models. - Innovating for state-of-the-art architectures involving Panoptic Segmentation, Image Classification, and Image Generation. - Designing, developing, and innovating state-of-the-art large multimodal models. - Executing training and inference processes to minimize latency and maximize throughput utilizing GPU clusters and custom hardware. - Integrating and tailoring frameworks like PyTorch, TensorFlow, DeepSpeed, Lightening, FSDP, and Habana for fast model training and inference. - Enhancing post-deployment mechanisms with exhaustive testing, real-time monitoring, and robustness checks. - Driving continuous improvement initiatives for deployed models with automated pipelines for drift detection and performance degradation. - Leading the charge in model management including version control, reproducibility, and lineage tracking. - Cultivating a culture of high-performance computing and optimization within the AI/ML domain. Qualifications: - Ph.D. with 5+ years or MS with 8+ years of experience in ML Engineering, Data Science, or related fields. - Demonstrated expertise in high-performance computing with proficiency in Python, C/C++, CUDA, and kernel-level programming for AI applications. - Extensive experience in optimizing training and inference for large-scale AI models. - Understanding of Diffusion Models, Variational Autoencoders, Bayesian Modelling, and Reinforcement Learning is beneficial. - Experience in building billions of parameters generative AI foundation models. - Proven success in deploying optimized ML systems on a large scale using cloud infrastructures and GPU resources. - In-depth understanding and hands-on experience with advanced model optimization frameworks and MLOps tools. - Familiarity with contemporary MLOps frameworks and their application in production environments. - Strong grasp of state-of-the-art ML infrastructures, deployment strategies, and optimization methodologies. - Innovative problem-solving skills and collaborative mindset. - Exceptional communication and team collaboration skills.,

National Payment Corporation of India (NPCI) is hiring Data Scientist (with Deep Learning Experience) Job Title: Data Scientist (Deep Learning Strong experience) Experience: 2 Years to 8 Years MUST HAVE SKILLS REQUIRED: (STRONG) Programming & DH : Python, Data Structures, Algorithms (STRONG) Data Handling : Python, EDA, Statistics, Probability Distributions (STRONG) Learning & Deep Learning : TensorFlow, PyTorch, GANs, Transformers (STRONG) Cloud & GPU: GCP, GPU-based machines, Model Optimization (STRONG) Model Lifecycle : Custom Loss Functions, Evaluation Metrics, Scalability If you find yourself Perfectly fit based on above skillset criteria. Please share your Updated resume at vinayak.ojha_ori@npci.org.in Overview: NPCI Data Analytics team is seeking a talented and motivated Data Scientist to join our team. As a Data Scientist, you will play a crucial role in modelling complex problems, uncovering insights, and identifying new opportunities through the use of statistical, algorithmic, mining, and visualization techniques. You will be focused on utilizing NPCI product data and analytics to solve business problems by applying machine learning and deep learning techniques, conducting statistical analysis, and building high-quality predictive systems that are integrated with our services. Key Responsibilities: Develop and implement deep learning models for various applications. Work with large datasets and perform exploratory data analysis. Develop custom loss functions and evaluation metrics. Collaborate with cross-functional teams to ensure successful deployment of models. Optimize models for performance, scalability, and efficiency. Conduct research and stay up to date with the latest developments in the field of deep learning. Participate in code reviews and provide feedback to team members. Qualifications: Bachelor's or Master's degree in Computer Science, Mathematics, or related field with 3+ years of experience. Strong proficiency in Python programming language. Good understanding of data structures and algorithms. Strong understanding of statistics and probability distributions Hands-on Experience with GANs and Transformers Experience with both Tensorflow and Pytorch frameworks. Familiarity with Google Cloud Platform (GCP) and working on GPU based machines. Strong problem-solving skills. Excellent written and verbal communication skills. Ability to work independently as well as in a team environment. Strong Communication skills and ability to simplify complex information and results into simple concepts and actionable insights for a variety of audiences.

Description We are seeking a skilled Computer Vision Engineer to join our team in India. The ideal candidate will have extensive experience in developing and implementing computer vision solutions, contributing to innovative projects that leverage advanced imaging technologies. Responsibilities Develop and implement computer vision algorithms for various applications. Collaborate with cross-functional teams to integrate computer vision solutions into products. Conduct research to improve existing computer vision models and frameworks. Analyze and preprocess image and video data for training machine learning models. Optimize computer vision algorithms for performance and efficiency. Stay updated with the latest trends and advancements in computer vision technologies. Skills and Qualifications 6-12 years of experience in computer vision or related fields. Strong proficiency in programming languages such as Python, C++, or Java. Experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras. Solid understanding of machine learning and statistical modeling techniques. Knowledge of image processing libraries like OpenCV, PIL, or scikit-image. Experience with computer vision tasks such as object detection, image segmentation, and facial recognition. Familiarity with cloud platforms and GPU programming for scalable model training. Strong analytical and problem-solving skills.

Position Overview : We are seeking an experienced NLP & LLM Specialist to join our team. The ideal candidate will have deep expertise in working with transformer-based models, including GPT, BERT, T5,RoBERTa, and similar models. This role requires experience in fine-tuning these pre-trained models on domain-specific tasks, as well as crafting and optimizing prompts for natural language processing tasks such as text generation, summarization, question answering, classification, and translation. The candidate should be proficient in Python and familiar with NLP libraries like Hugging Face, SpaCy, and NLTK, with a solid understanding of model evaluation metrics. Roles and Responsibilities : Model Expertise : Work with transformer models such as GPT, BERT, T5, RoBERTa, and others for a variety of NLP tasks, including text generation, summarization, classification, and translation. Model Fine-Tuning: Fine-tune pre-trained models on domain-specific datasets to improve performance for specific applications such as summarization, text generation, and question answering. Prompt Engineering: Craft clear, concise, and contextually relevant prompts to guide transformer-based models towards generating desired outputs for specific tasks. Iterate on prompts to optimize model performance. Instruction-Based Prompting: Implement instruction-based prompting to guide the model toward achieving specific goals, ensuring that the outputs are contextually accurate and aligned with task objectives. Zero-shot, Few-shot, Many-shot Learning: Utilize zero-shot, few-shot, and many-shot learning techniques to improve model performance without the need for full retraining. Chain-of-Thought (CoT) Prompting: Implement Chain-of-Thought (CoT) prompting to guide models through complex reasoning tasks, ensuring that the outputs are logically structured and provide step-by-step explanations. Model Evaluation: Use evaluation metrics such as BLEU, ROUGE, and other relevant metrics to assess and improve the performance of models for various NLP tasks. Model Deployment: Support the deployment of trained models into production environments and integrate them into existing systems for real-time applications. Bias Awareness: Be aware of and mitigate issues related to bias, hallucinations, and knowledge cutoffs in LLMs, ensuring high-quality and reliable outputs. Collaboration: Collaborate with cross-functional teams including engineers, data scientists, and product managers to deliver efficient and scalable NLP solutions. Must Have Skill : Overall 7 years with at least 5+ years of experience working with transformer-based models and NLP tasks, with a focus on text generation, summarization, question answering, classification, and similar tasks. Expertise in transformer models like GPT (Generative Pre-trained Transformer), BERT (Bidirectional Encoder Representations from Transformers), T5 (Text-to-Text Transfer Transformer), RoBERTa, and similar models. Familiarity with model architectures, attention mechanisms, and self-attention layers that enable LLMs to generate human-like text. Experience in fine-tuning pre-trained models on domain-specific datasets for tasks such as text generation, summarization, question answering, classification, and translation. Familiarity with concepts like attention mechanisms, context windows, tokenization, and embedding layers. Awareness of biases, hallucinations, and knowledge cutoffs that can affect LLM performance and output quality. Expertise in crafting clear, concise, and contextually relevant prompts to guide LLMs towards generating desired outputs. Experience in instruction-based prompting Use of zero-shot, few-shot, and many-shot learning techniques for maximizing model performance without retraining. Experience in iterating on prompts to refine outputs, test model performance, and ensure consistent results. Crafting prompt templates for repetitive tasks, ensuring prompts are adaptable to different contexts and inputs. Expertise in chain-of-thought (CoT) prompting to guide LLMs through complex reasoning tasks by encouraging step-by-step breakdowns. Proficiency in Python and experience with NLP libraries (e.g , Hugging Face, SpaCy, NLTK). Experience with transformer-based models (e.g , GPT, BERT, T5) for text generation tasks. Experience in training, fine-tuning, and deploying machine learning models in an NLP context. Understanding of model evaluation metrics (e.g , BLEU, ROUGE) Qualification : BE/B.Tech or Equivalent degree in Computer Science or related field. Excellent communication skills in English, both verbal and written.

Responsibilities Generative AI Development: Lead the design and development of cutting-edge generative AI systems using Azure cloud services and OpenAI technologies. Focus on building efficient, scalable architectures that incorporate the latest techniques, such as transformer-based architectures and foundation models like GPT-4 and beyond. Multimodal AI Integration: Work with multimodal AI systems that can process and generate across various data types (text, images, audio, and video), leveraging large-scale embeddings and cross-modal understanding. Apply advances in diffusion models, synthetic data generation, and foundation models. Foundation Model Fine-Tuning: Apply extensive experience in fine-tuning large language models (LLMs) and foundation models, particularly those used in embeddings and vector space models. Adapt these models for specific applications, improving their efficiency and accuracy in understanding complex data structures. Azure and OpenAI Integration: Manage and optimize the deployment of generative AI projects on Azure, ensuring robust integration with OpenAI's APIs and tools. Leverage cloud-native architectures to build AI solutions that scale. Advanced Python and AI Framework Expertise: Master Python programming within the context of modern AI and machine learning libraries (e.g., PyTorch, TensorFlow, Hugging Face). Focus on developing and manipulating embeddings and vector space models using the latest advancements in machine learning and AI tools. Embeddings and Vector Space Mastery: Demonstrate deep knowledge of embedding techniques and vector space models, especially in the context of generative AI. Implement state-of-the-art strategies for creating, optimizing, and utilizing embeddings for various data types (e.g., large-scale text, images, audio). AI-Driven Personalization & Search: Lead initiatives that utilize embeddings and generative AI to develop personalized solutions, advanced search algorithms, and recommendations, leveraging AI for better data understanding and user interaction. Responsible AI & Ethics: Uphold and advocate for the responsible use of AI technologies, including ethical AI development, data privacy, bias mitigation, and alignment with compliance standards such as HIPAA, GDPR, and other relevant regulations. Model Optimization & Monitoring: Continuously optimize generative AI models, focusing on vector space efficiency, inference speed, and memory management in large-scale AI applications. Apply the latest techniques in model distillation, pruning, and efficient finetuning. Thought Leadership & Mentorship: Stay at the forefront of generative AI developments, including advancements in embeddings, LLMs, and foundation models. Mentor team members and drive knowledge sharing across interdisciplinary teams. Risk Management & Governance: Evaluate risks in generative AI initiatives, with a particular focus on embeddings and vector space models. Implement strategies to mitigate risks associated with AI model usage and performance, including ethical considerations in AI applications. Competencies Advanced degree in Computer Science, AI, Machine Learning, or a related field. Extensive experience in developing generative AI systems, with particular expertise in embeddings, vector space models, and multimodal AI. Proficiency in Python and relevant AI/ML libraries (e.g., PyTorch, TensorFlow, Hugging Face). Demonstrated experience working with Azure and OpenAI platforms, including fine-tuning and deploying large models. Strong analytical, leadership, and communication skills with a track record of successful collaboration across interdisciplinary teams. Commitment to responsible AI practices, with knowledge of AI ethics and compliance standards (HIPAA, GDPR, etc.).

We are seeking an experienced Gen AI and LLM Developer to design, develop, and deploy generative AI models and large language models (LLMs) for advanced natural language processing (NLP) tasks. The ideal candidate will have 6-9 years of experience with LLM architectures (e.g., GPT, BERT), deep learning frameworks (PyTorch, TensorFlow), and cloud platforms (AWS, GCP, Azure). Responsibilities include training and fine-tuning models, optimizing for performance, collaborating with cross-functional teams, and staying updated on the latest AI trends. Strong technical skills in Python, NLP techniques, model optimization, and distributed training are essential.Experience designing scalable system with Generative AI" and "Exposure to full stack development on .net or Java based platform

Qualification Design, develop, and deploy machine learning and deep learning modls. Collaborate with data scientists, product managers, and engineers to identify opportunities for AI integration. Build scalable and efficient data pipelines to train and serve AI models. Optimize models for performance, accuracy, and resource efficiency. Monitor and maintain production AI systems, ensuring reliability and performance. Research and prototype new AI techniques and stay current with the latest advancements in AI and ML. Document models, processes, and methodologies clearly and concisely.

Qualification Design, develop, and deploy machine learning and deep learning modls. Collaborate with data scientists, product managers, and engineers to identify opportunities for AI integration. Build scalable and efficient data pipelines to train and serve AI models. Optimize models for performance, accuracy, and resource efficiency. Monitor and maintain production AI systems, ensuring reliability and performance. Research and prototype new AI techniques and stay current with the latest advancements in AI and ML. Document models, processes, and methodologies clearly and concisely.

We are a pioneering company dedicated to Revolutionizing autism with AI-driven solutions. Role: Develop AI models using Python and TensorFlow Implement machine learning algorithms Collaborate with data scientists to enhance AI systems Required Candidate profile Optimize AI solutions for performance Integrate AI with business applications Stay updated on AI advancements.