21 Dvc Jobs

As an AI / ML Engineer, you will be responsible for utilizing your expertise in the field of Artificial Intelligence and Machine Learning to develop innovative solutions. You should hold a Bachelor's or Master's degree in Computer Science, Engineering, Data Science, AI/ML, Mathematics, or a related field. With a minimum of 6 years of experience in AI/ML, you are expected to demonstrate proficiency in Python and various ML libraries such as scikit-learn, XGBoost, pandas, NumPy, matplotlib, and seaborn. In this role, you will need a strong understanding of machine learning algorithms and deep learning architectures including CNNs, RNNs, and Transformers. Hands-on experience with TensorFlow, PyTorch, or Keras is essential. You should also have expertise in data preprocessing, feature selection, exploratory data analysis (EDA), and model interpretability. Additionally, familiarity with API development and deploying models using frameworks like Flask, FastAPI, or similar tools is required. Experience with MLOps tools such as MLflow, Kubeflow, DVC, and Airflow will be beneficial. Knowledge of cloud platforms like AWS (SageMaker, S3, Lambda), GCP (Vertex AI), or Azure ML is preferred. Proficiency in version control using Git, CI/CD processes, and containerization with Docker is essential for this role. Bonus skills that would be advantageous include familiarity with NLP frameworks (e.g., spaCy, NLTK, Hugging Face Transformers), Computer Vision experience using OpenCV or YOLO/Detectron, and knowledge of Reinforcement Learning or Generative AI (GANs, LLMs). Experience with vector databases such as Pinecone or Weaviate, as well as LangChain for AI agent building, is a plus. Familiarity with data labeling platforms and annotation workflows will also be beneficial. In addition to technical skills, you should possess soft skills such as an analytical mindset, strong problem-solving abilities, effective communication, and collaboration skills. The ability to work independently in a fast-paced, agile environment is crucial. A passion for AI/ML and a proactive approach to staying updated with the latest developments in the field are highly desirable for this role.,

???? Were Hiring: AI Engineer ???? Location: Bengaluru (Regular office-based role) ???? Employment Type: Full-Time | 5 Days a Week from Office ???? Qualification: B.E / B.Tech or equivalent degree in Computer Science, IT, or related field Are you passionate about building and scaling production-grade AI/ML systems We&aposre looking for a skilled AI Engineer to join our team in Bengaluru and help drive real-world impact through cutting-edge machine learning and GenAI technologies. ???? Must-Have Skills: 48 years of hands-on experience in designing, building, and deploying production-grade AI/ML solutions Proficiency in Python, PySpark, SQL , and ML libraries like Scikit-learn, XGBoost, LightGBM Cloud-native ML development experience on AWS (SageMaker), GCP (Vertex AI), or Azure ML Strong background in NLP/GenAI frameworks: Hugging Face, LangChain, LlamaIndex Practical knowledge of MLOps tools (MLflow, Weights & Biases, DVC) and deployment frameworks ( FastAPI, Flask, Docker, Kubernetes ) Excellent communication, stakeholder engagement, and team collaboration skills Good-to-Have: Publications, blog posts, or open-source contributions in AI/ML Experience leading AI strategy or owning technical roadmaps Show more Show less

About the Role: We are seeking an experienced MLOps Engineer to lead the deployment, scaling, and performance optimization of open-source Generative AI models on cloud infrastructure. Youll work at the intersection of machine learning, DevOps, and cloud engineering to help productize and operationalize large-scale LLM and diffusion models. Key Responsibilities: Design and implement scalable deployment pipelines for open-source Gen AI models (LLMs, diffusion models, etc.). Fine-tune and optimize models using techniques like LoRA, quantization, distillation, etc. Manage inference workloads, latency optimization, and GPU utilization. Build CI/CD pipelines for model training, validation, and deployment. Integrate observability, logging, and alerting for model and infrastructure monitoring. Automate resource provisioning using Terraform, Helm, or similar tools on GCP/AWS/Azure. Ensure model versioning, reproducibility, and rollback using tools like MLflow, DVC, or Weights & Biases. Collaborate with data scientists, backend engineers, and DevOps teams to ensure smooth production rollouts. Required Skills & Qualifications: 5+ years of total experience in software engineering or cloud infrastructure. 3+ years in MLOps with direct experience in deploying large Gen AI models. Hands-on experience with open-source models (e.g., LLaMA, Mistral, Stable Diffusion, Falcon, etc.). Strong knowledge of Docker, Kubernetes, and cloud compute orchestration. Proficiency in Python and familiarity with model-serving frameworks (e.g., FastAPI, Triton Inference Server, Hugging Face Accelerate, vLLM). Experience with cloud platforms (GCP preferred, AWS or Azure acceptable). Familiarity with distributed training, checkpointing, and model parallelism. Good to Have: Experience with low-latency inference systems and token streaming architectures. Familiarity with cost optimization and scaling strategies for GPU-based workloads. Exposure to LLMOps tools (LangChain, BentoML, Ray Serve, etc.). Why Join Us: Opportunity to work on cutting-edge Gen AI applications across industries. Collaborative team with deep expertise in AI, cloud, and enterprise software. Flexible work environment with a focus on innovation and impact. Show more Show less

You are an experienced Senior DevOps/MLOps Engineer who will be responsible for leading and managing a high-performing engineering team. Your main focus will be on overseeing the deployment and scaling of machine learning models and backend services using modern DevOps and MLOps practices. It is essential that you have proficiency in FastAPI, Docker, Kubernetes, and CI/CD. Your key responsibilities will include guiding and managing a team of DevOps/MLOps engineers, optimizing, containerizing, and deploying FastAPI applications at scale, managing infrastructure using tools like Terraform or Helm, handling multi-environment Kubernetes clusters (GKE, EKS, AKS, or on-prem), managing ML model lifecycle including versioning, deployment, monitoring, and rollback, designing and maintaining robust CI/CD pipelines for model and application deployment, setting up observability tools such as Prometheus, Grafana, ELK, ensuring secure infrastructure and data pipelines. Your required skills should include a deep understanding of building, scaling, and securing APIs with FastAPI, expert-level experience in Docker and Kubernetes for containerization and orchestration, familiarity with CI/CD tools like GitHub Actions, GitLab CI, Jenkins, ArgoCD, or similar, experience with cloud platforms such as AWS/GCP/Azure, strong scripting and automation skills with Python, and knowledge of ML Workflow Tools like MLflow, DVC, Kubeflow, or Seldon. Preferred qualifications for this role include experience in managing hybrid cloud/on-premise deployments, strong communication and mentoring skills, and an understanding of data pipelines, feature stores, and model drift monitoring. This is a full-time, permanent position that requires in-person work location.,

computer vision or deep learning roles industrial/safety inspection datasets (e.g., PPE detection, visual defect classification). Familiarity with MLOps tools like MLflow, DVC, or ClearML. ONNX, TensorRT, OpenVINO

We are seeking a skilled and driven AI Developer to create, implement, and launch advanced machine learning models and artificial intelligence solutions. The ideal candidate will possess strong programming abilities, a profound comprehension of machine learning algorithms, and proficiency in model deployment and refinement. Your primary responsibilities will include crafting and executing ML models and AI solutions utilizing suitable algorithms, examining extensive datasets to extract valuable patterns for business decisions, and refining machine learning models to ensure optimal performance. You will also be involved in constructing pipelines for data preprocessing, model training, testing, and deployment, as well as integrating ML models into production through REST APIs, Docker, or cloud services (e.g., AWS SageMaker, GCP AI Platform, Azure ML). Monitoring and enhancing model accuracy, scalability, and dependability post-deployment will also be part of your duties. Collaboration with cross-functional teams comprising product, engineering, and data science professionals to incorporate ML solutions into existing systems is crucial. You will be expected to research and implement new AI methodologies while staying abreast of the latest trends in the field. The ideal candidate should hold a Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or a related field. Proficiency in Python and libraries like TensorFlow, PyTorch, and Scikit-learn is essential. A solid grasp of supervised, unsupervised, and reinforcement learning techniques is required, along with experience in NLP, computer vision, or time-series forecasting projects. Familiarity with data processing tools such as Pandas, NumPy, and SQL is expected, as well as knowledge of statistics, linear algebra, and probability theory. Experience in deploying models using Flask/FastAPI, Docker, and CI/CD pipelines is preferred. Familiarity with cloud platforms like AWS, GCP, or Azure, as well as proficiency in version control systems (Git) and collaborative tools like JIRA and Confluence, are advantageous. Hands-on experience with MLOps practices, model monitoring tools, Hugging Face Transformers, OpenCV, YOLO, and similar tools will be beneficial. Participation in Kaggle competitions, published papers, or GitHub AI/ML projects is considered a strong advantage. This is a full-time position located in Nagpur with a salary as per market standards. The ideal candidate should have 2-4 years of experience and be below 35 years old. Educational requirements include a Bachelors or Masters degree or equivalent in a relevant field. Proficiency in English and Hindi is required. Please note that there are no specific perks and benefits mentioned for this position.,

As a high-impact AI/ML Engineer, you will lead the design, development, and deployment of machine learning and AI solutions across vision, audio, and language modalities. You will be an integral part of a fast-paced, outcome-oriented AI & Analytics team, collaborating with data scientists, engineers, and product leaders to translate business use cases into real-time, scalable AI systems. Your responsibilities in this role will include architecting, developing, and deploying ML models for multimodal problems encompassing vision, audio, and NLP tasks. You will be responsible for the complete ML lifecycle, from data ingestion to model development, experimentation, evaluation, deployment, and monitoring. Leveraging transfer learning and self-supervised approaches where appropriate, you will design and implement scalable training pipelines and inference APIs using frameworks like PyTorch or TensorFlow. Collaborating with MLOps, data engineering, and DevOps teams, you will operationalize models using technologies such as Docker, Kubernetes, or serverless infrastructure. Continuously monitoring model performance and implementing retraining workflows to ensure sustained accuracy over time will be a key aspect of your role. You will stay informed about cutting-edge AI research and incorporate innovations such as generative AI, video understanding, and audio embeddings into production systems. Writing clean, well-documented, and reusable code to support agile experimentation and long-term platform development is an essential part of this position. To qualify for this role, you should hold a Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field, with a minimum of 5-8 years of experience in AI/ML Engineering, including at least 3 years in applied deep learning. In terms of technical skills, you should be proficient in Python, with knowledge of R or Java being a plus. Additionally, you should have expertise in ML/DL Frameworks like PyTorch, TensorFlow, and Scikit-learn, as well as experience in Computer Vision tasks such as image classification, object detection, OCR, segmentation, and tracking. Familiarity with Audio AI tasks like speech recognition, sound classification, and audio embedding models is also desirable. Strong capabilities in Data Engineering using tools like Pandas, NumPy, SQL, and preprocessing pipelines for structured and unstructured data are required. Knowledge of NLP/LLMs, Cloud & MLOps services, deployment & infrastructure technologies, and CI/CD & Version Control tools are also beneficial. Soft skills and competencies that will be valuable in this role include strong analytical and systems thinking, effective communication skills to convey models and results to non-technical stakeholders, the ability to work cross-functionally with various teams, and a demonstrated bias for action, rapid experimentation, and iterative delivery of impact.,

Ready to build the future with AI At Genpact, we don&rsquot just keep up with technology&mdashwe set the pace. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos , our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to , our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, innovation-driven environment, love building and deploying cutting-edge AI solutions, and want to push the boundaries of what&rsquos possible, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation , our teams implement data, technology, and AI to create tomorrow, today. Get to know us at and on , , , and . Inviting applications for the role of Senior Manager , Data Scientist We are seeking a tenured and highly skilled Data Scientist with deep expertise in Computer Vision and a strong foundation in AI/ML modeling. The ideal candidate will not only lead the development of intelligent vision systems but will also serve as a technical mentor, providing guidance to junior data scientists on model selection, optimization, and deployment strategies. Experience in domains such as energy, power generation, industrial equipment, or manufacturing will be considered a strong advantage, as the role involves solving real-world visual AI /ML problems in industrial environments. Key Responsibilities: Lead CV Projects: Design and deliver Computer Vision models across a range of use cases (e.g., anomaly detection, visual inspections, OCR, predictive maintenance). Model Development: Develop, evaluate, and optimize state-of-the-art AI/ML models (e.g., CNNs, Vision Transformers, YOLO, Faster R-CNN, etc.). Mentorship: Guide junior and mid-level data scientists on best practices in feature engineering, model selection, evaluation metrics, and problem-solving strategies. Domain Translation: Translate complex industrial problems into AI-driven CV solutions that can scale in production environments. Collaboration: Work closely with software engineers, MLOps , and business teams to ensure model integration and operational success. Code Quality & Experimentation: Drive code modularity, reproducibility, and experimentation through use of ML pipelines, version control, and testing. Innovation & Research: Stay current with latest CV and AI/ML advancements and apply them appropriately to business problems. Stakeholder Communication: Present insights, models, and outcomes in a clear and impactful way to both technical and non-technical stakeholders. Required Qualifications: Master&rsquos or PhD in Computer Science, Machine Learning, AI, Electrical Engineering, or a related field. Sound experience in building and deploying machine learning models, with a strong portfolio in Computer Vision. Deep expertise in ML frameworks and CV libraries such as PyTorch , TensorFlow, OpenCV, Detectron2, MMDetection , etc. Solid understanding of core AI/ML algorithms - classification, regression, segmentation, object detection, time-series, clustering, etc. Experience with MLOps tools (e.g., MLflow , DVC, Kubeflow) and cloud platforms (AWS/GCP/Azure). Strong communication , leadership, and team collaboration skills . Preferred Qualifications: Prior experience in domains such as energy, utilities, power generation, or industrial systems is highly preferred. Experience deploying CV models within real-time environments. Contributions to open-source CV projects or published research. Why join Genpact Lead AI-first transformation - Build and scale AI solutions that redefine industries Make an impact - Drive change for global enterprises and solve business challenges that matter Accelerate your career &mdashGain hands-on experience, world-class training, mentorship, and AI certifications to advance your skills Grow with the best - Learn from top engineers, data scientists, and AI experts in a dynamic, fast-moving workplace Committed to ethical AI - Work in an environment where governance, transparency, and security are at the core of everything we build Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the 140,000+ coders, tech shapers, and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color , religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

As an AI Ops Expert, you will be responsible for the delivery of projects with defined quality standards within set timelines and budget constraints. Your role will involve managing the AI model lifecycle, versioning, and monitoring in production environments. You will be tasked with building resilient MLOps pipelines and ensuring adherence to governance standards. Additionally, you will design, implement, and oversee AIops solutions to automate and optimize AI/ML workflows. Collaboration with data scientists, engineers, and stakeholders will be essential to ensure seamless integration of AI/ML models into production systems. Monitoring and maintaining the health and performance of AI/ML systems, as well as developing and maintaining CI/CD pipelines for AI/ML models, will also be part of your responsibilities. Troubleshooting and resolving issues related to AI/ML infrastructure and workflows will require your expertise, along with staying updated on the latest AI Ops, MLOps, and Kubernetes tools and technologies. To be successful in this role, you must possess a Bachelor's or Master's degree in Computer Science, Software Engineering, or a related field, along with at least 8 years of relevant experience. Your proven experience in AIops, MLOps, or related fields will be crucial. Proficiency in Python and hands-on experience with Fast API are required, as well as strong expertise in Docker and Kubernetes (or AKS). Familiarity with MS Azure and its AI/ML services, including Azure ML Flow, is essential. Additionally, you should be proficient in using DevContainer for development and have knowledge of CI/CD tools like Jenkins, Argo CD, Helm, GitHub Actions, or Azure DevOps. Experience with containerization and orchestration tools, Infrastructure as Code (Terraform or equivalent), strong problem-solving skills, and excellent communication and collaboration abilities are also necessary. Preferred skills for this role include experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn, as well as familiarity with data engineering tools like Apache Kafka, Apache Spark, or similar. Knowledge of monitoring and logging tools such as Prometheus, Grafana, or ELK stack, along with an understanding of data versioning tools like DVC or MLflow, would be advantageous. Proficiency in Azure-specific tools and services like Azure Machine Learning (Azure ML), Azure DevOps, Azure Kubernetes Service (AKS), Azure Functions, Azure Logic Apps, Azure Data Factory, Azure Monitor, and Application Insights is also preferred. Joining our team at Socit Gnrale will provide you with the opportunity to be part of a dynamic environment where your contributions can make a positive impact on the future. You will have the chance to innovate, collaborate, and grow in a supportive and stimulating setting. Our commitment to diversity and inclusion, as well as our focus on ESG principles and responsible practices, ensures that you will have the opportunity to contribute meaningfully to various initiatives and projects aimed at creating a better future for all. If you are looking to be directly involved, develop your expertise, and be part of a team that values collaboration and innovation, you will find a welcoming and fulfilling environment with us at Socit Gnrale.,

As a Machine Learning Engineer at our company, you will be utilizing your expertise in Computer Vision, Natural Language Processing (NLP), and Backend Development. Your primary responsibilities will include developing ML/DL models for Computer Vision tasks such as classification, object detection, and segmentation, as well as for NLP tasks like text classification, Named Entity Recognition (NER), and summarization. You will also be implementing research papers and creating production-ready prototypes. To excel in this role, you must have a solid understanding of Machine Learning and Deep Learning concepts. Proficiency in tools and libraries like PyTorch, OpenCV, Pillow, TorchVision, and Transformers is essential. You will be optimizing models using techniques such as quantization, pruning, ONNX export, and TorchScript. Moreover, you will be tasked with building and deploying RESTful APIs using FastAPI, Flask, or Django, and containerizing applications using Docker for deployment on cloud or local servers. Your role will also involve writing clean, efficient, and scalable code for backend and ML pipelines. Strong backend skills using FastAPI, Flask, or Django are required, along with experience in utilizing NLP libraries like Hugging Face Transformers, spaCy, and NLTK. Familiarity with Docker, Git, and Linux environments is crucial for this position, as well as experience with model deployment and optimization tools such as ONNX and TorchScript. While not mandatory, it would be advantageous to have knowledge of Generative AI / Large Language Models (LLMs) and experience with MLOps tools like MLflow, DVC, and Airflow. Additionally, familiarity with cloud platforms such as AWS, GCP, or Azure would be a plus. The ideal candidate should hold a Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or a related field. This is a full-time position with an evening shift schedule from Monday to Friday. The work location is in person.,

You will be responsible for developing machine learning models by designing, building, and evaluating both supervised and unsupervised models like regression, classification, clustering, and recommendation systems. This includes performing feature engineering, model tuning, and validation through cross-validation and various performance metrics. Your duties will also involve preparing and analyzing data by cleaning, preprocessing, and transforming large datasets sourced from different channels. You will conduct exploratory data analysis (EDA) to reveal patterns and gain insights from the data. In addition, you will deploy machine learning models into production using tools like Flask, FastAPI, or cloud-native services. Monitoring model performance and updating or retraining models as necessary will also fall under your purview. Collaboration and communication are key aspects of this role as you will collaborate closely with data engineers, product managers, and business stakeholders to comprehend requirements and provide impactful solutions. Furthermore, presenting findings and model outcomes in a clear and actionable manner will be essential. You will utilize Python and libraries such as scikit-learn, XGBoost, TensorFlow, or PyTorch. Additionally, leveraging version control tools like Git, Jupyter notebooks, and ML lifecycle tools such as MLflow and DVC will be part of your daily tasks. The ideal candidate should possess a Bachelor's or Master's degree in computer science, Data Science, Statistics, or a related field. A minimum of 2-3 years of experience in building and deploying machine learning models is preferred. Strong programming skills in Python and familiarity with SQL are required. A solid grasp of ML concepts, model evaluation, statistical techniques, exposure to cloud platforms (AWS, GCP, or Azure), and MLOps practices would be advantageous. Excellent problem-solving and communication skills are also essential for this role.,

As a Machine Learning Engineer, you will be responsible for designing and implementing scalable machine learning models throughout the entire lifecycle - from data preprocessing to deployment. Your role will involve leading feature engineering and model optimization efforts to enhance performance and accuracy. Additionally, you will build and manage end-to-end ML pipelines using MLOps practices, ensuring seamless deployment, monitoring, and maintenance of models in production environments. Collaboration with data scientists and product teams will be key in understanding business requirements and translating them into effective ML solutions. You will conduct advanced data analysis, create visualization dashboards for insights, and maintain detailed documentation of models, experiments, and workflows. Moreover, mentoring junior team members on best practices and technical skills will be part of your responsibilities to foster growth within the team. In terms of required skills, you must have at least 3 years of experience in machine learning development, with a focus on the end-to-end model lifecycle. Proficiency in Python using Pandas, NumPy, and Scikit-learn for advanced data handling and feature engineering is crucial. Strong hands-on expertise in TensorFlow or PyTorch for deep learning model development is also a must-have. Desirable skills include experience with MLOps tools like MLflow or Kubeflow for model management and deployment, familiarity with big data frameworks such as Spark or Dask, and exposure to cloud ML services like AWS SageMaker or GCP AI Platform. Additionally, working knowledge of Weights & Biases and DVC for experiment tracking and versioning, as well as experience with Ray or BentoML for distributed training and model serving, will be considered advantageous. Join our team and contribute to cutting-edge machine learning projects while continuously improving your skills and expertise in a collaborative and innovative environment.,

Ready to shape the future of work At Genpact, we don&rsquot just adapt to change&mdashwe drive it. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos , our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to , our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that&rsquos shaping the future, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation , our teams implement data, technology, and AI to create tomorrow, today. Get to know us at and on , , , and . Inviting applications for the role of Lead Consultant - ML/CV Ops Engineer ! We are seeking a highly skilled ML CV Ops Engineer to join our AI Engineering team. This role is focused on operationalizing Computer Vision models&mdashensuring they are efficiently trained, deployed, monitored , and retrained across scalable infrastructure or edge environments. The ideal candidate has deep technical knowledge of ML infrastructure, DevOps practices, and hands-on experience with CV pipelines in production. You&rsquoll work closely with data scientists, DevOps, and software engineers to ensure computer vision models are robust, secure, and production-ready always. Key Responsibilities: End-to-End Pipeline Automation: Build and maintain ML pipelines for computer vision tasks (data ingestion, preprocessing, model training, evaluation, inference). Use tools like MLflow , Kubeflow, DVC, and Airflow to automate workflows. Model Deployment & Serving: Package and deploy CV models using Docker and orchestration platforms like Kubernetes. Use model-serving frameworks (TensorFlow Serving, TorchServe , Triton Inference Server) to enable real-time and batch inference. Monitoring & Observability: Set up model monitoring to detect drift, latency spikes, and performance degradation. Integrate custom metrics and dashboards using Prometheus, Grafana, and similar tools. Model Optimization: Convert and optimize models using ONNX, TensorRT , or OpenVINO for performance and edge deployment. Implement quantization, pruning, and benchmarking pipelines. Edge AI Enablement (Optional but Valuable): Deploy models on edge devices (e.g., NVIDIA Jetson, Coral, Raspberry Pi) and manage updates and logs remotely. Collaboration & Support: Partner with Data Scientists to productionize experiments and guide model selection based on deployment constraints. Work with DevOps to integrate ML models into CI/CD pipelines and cloud-native architecture. Qualifications we seek in you! Minimum Qualifications Bachelor&rsquos or Master&rsquos in Computer Science , Engineering, or a related field. Sound experience in ML engineering, with significant work in computer vision and model operations. Strong coding skills in Python and familiarity with scripting for automation. Hands-on experience with PyTorch , TensorFlow, OpenCV, and model lifecycle tools like MLflow , DVC, or SageMaker. Solid understanding of containerization and orchestration (Docker, Kubernetes). Experience with cloud services (AWS/GCP/Azure) for model deployment and storage. Preferred Qualifications: Experience with real-time video analytics or image-based inference systems. Knowledge of MLOps best practices (model registries, lineage, versioning). Familiarity with edge AI deployment and acceleration toolkits (e.g., TensorRT , DeepStream ). Exposure to CI/CD pipelines and modern DevOps tooling (Jenkins, GitLab CI, ArgoCD ). Contributions to open-source ML/CV tooling or experience with labeling workflows (CVAT, Label Studio). Why join Genpact Be a transformation leader - Work at the cutting edge of AI, automation, and digital innovation Make an impact - Drive change for global enterprises and solve business challenges that matter Accelerate your career - Get hands-on experience, mentorship, and continuous learning opportunities Work with the best - Join 140,000+ bold thinkers and problem-solvers who push boundaries every day Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color , religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

Ready to shape the future of work At Genpact, we don&rsquot just adapt to change&mdashwe drive it. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos , our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to , our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that&rsquos shaping the future, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation , our teams implement data, technology, and AI to create tomorrow, today. Get to know us at and on , , , and . Inviting applications for the role of Senior Principal Consultant - Data Scientists with Computer vision experience! We are seeking a tenured and highly skilled Data Scientist with deep expertise in Computer Vision and a strong foundation in AI/ML modeling. The ideal candidate will not only lead the development of intelligent vision systems but will also serve as a technical mentor, providing guidance to junior data scientists on model selection, optimization, and deployment strategies. Experience in domains such as energy, power generation, industrial equipment, or manufacturing will be considered a strong advantage, as the role involves solving real-world visual AI/ML problems in industrial environments. Key Responsibilities: Lead CV Projects: Design and deliver Computer Vision models across a range of use cases (e.g., anomaly detection, visual inspections, OCR, predictive maintenance). Model Development: Develop, evaluate, and optimize state-of-the-art AI/ML models (e.g., CNNs, Vision Transformers, YOLO, Faster R-CNN, etc.). Mentorship: Guide junior and mid-level data scientists on best practices in feature engineering, model selection, evaluation metrics, and problem-solving strategies. Domain Translation: Translate complex industrial problems into AI-driven CV solutions that can scale in production environments. Collaboration: Work closely with software engineers, MLOps , and business teams to ensure model integration and operational success. Code Quality & Experimentation: Drive code modularity, reproducibility, and experimentation through use of ML pipelines, version control, and testing. Innovation & Research: Stay current with latest CV and AI/ML advancements and apply them appropriately to business problems. Stakeholder Communication: Present insights, models, and outcomes in a clear and impactful way to both technical and non-technical stakeholders. Qualifications we seek in you! Minimum Qualifications Master&rsquos or PhD in Computer Science, Machine Learning, AI, Electrical Engineering, or a related field. industry experience in building and deploying machine learning models, with a strong portfolio in Computer Vision. Deep expertise in ML frameworks and CV libraries such as PyTorch , TensorFlow, OpenCV, Detectron2, MMDetection , etc. Solid understanding of core AI/ML algorithms - classification, regression, segmentation, object detection, time-series, clustering, etc. Experience with MLOps tools (e.g., MLflow , DVC, Kubeflow) and cloud platforms (AWS/GCP/Azure). Strong communication , leadership, and team collaboration skills . Preferred Qualifications: Prior experience in domains such as energy, utilities, power generation, or industrial systems is highly preferred. Experience deploying CV models within real-time environments. Contributions to open-source CV projects or published research. Proficient in statistical modelling, machine learning techniques, AI algorithms, and generative model development using large language models such as GPT-3, BERT, or similar frameworks like RAG, Knowledge Graphs etc. Lead the development of CI/CD pipelines and standardize deployment frameworks. Strong Python programming skills. Why join Genpact Be a transformation leader - Work at the cutting edge of AI, automation, and digital innovation Make an impact - Drive change for global enterprises and solve business challenges that matter Accelerate your career - Get hands-on experience, mentorship, and continuous learning opportunities Work with the best - Join 140,000+ bold thinkers and problem-solvers who push boundaries every day Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color , religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

Ready to shape the future of work At Genpact, we don&rsquot just adapt to change&mdashwe drive it. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos , our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to , our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that&rsquos shaping the future, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation , our teams implement data, technology, and AI to create tomorrow, today. Get to know us at and on , , , and . Inviting applications for the role of Principal Consultant - (AI App Ops Lead)! We are looking for a seasoned and hands-on Application Operations Lead to drive the operational excellence of Computer Vision (CV) applications. This individual will lead and mentor a team of ML CV Ops Engineers, ensuring the resilience, scalability, and reliability of AI-powered visual systems deployed in production environments. The ideal candidate will bring a blend of leadership, system operations, ML infrastructure knowledge, and cross-functional collaboration. You will be responsible for orchestrating the delivery, monitoring, and optimization of critical CV models and applications, deployed across cloud and edge environments. Key Responsibilities: Lead and mentor a team of ML CV Ops Engineers to manage the lifecycle of computer vision applications in production. Define and implement operational strategies, workflows, and performance goals for the App Ops team. Foster a DevOps/ MLOps culture of automation, ownership, and continuous improvement. Ensure production CV applications meet high availability, performance, and security standards. Establish SLAs, monitoring policies, and governance frameworks for mission-critical AI systems. Own the incident response process, drive root cause analysis, and coordinate remediation with CV engineering and data science teams. Maintain high observability through monitoring tools (e.g., Prometheus, Grafana, Datadog, AppDynamics). Partner with Data Scientists, MLOps , Cloud Engineers, and Software Developers to ensure smooth model deployments and robust CI/CD pipelines. Act as the technical operations bridge between AI model development and enterprise IT. Champion automation of repetitive support and operational tasks, including model validation, performance regression testing, and retraining triggers. Drive cost and resource optimization for cloud/GPU infrastructure used in CV workloads. Ensure operational practices adhere to audit, security, and regulatory compliance requirements. Maintain operational runbooks, escalation paths, and support documentation for CV systems. Define, Implement, Execute AI App Ops standard work Define KPIs for Support Ops performance and monitor and report on Support Ops KPIs Assist in issue analysis and remediation by developing standard work and investigate, troubleshoot, manage and resolve technical issues Develop code and implement proactive alerting mechanisms Establish and Monitor and act on observability metrics and thresholds Design and Develop proactive alerting mechanisms Create and Implement feedback loop for model observability data Configure and develop scalable pipeline for model integrations Implement observability metrics and thresholds Govern and Support change management processes Assist in knowledge transition and developing training materials Oversee and assist in investigation and resolution of vulnerabilities Transition knowledge from incumbent partner Qualifications we seek in you! Minimum Qualifications Bachelor&rsquos or Master&rsquos degree in Computer Science , Engineering, or a related field. experience in IT Operations, Site Reliability Engineering, or DevOps, with 2+ years in managing ML/AI systems in production. Proven experience in leading technical teams, preferably in ML Ops or platform engineering contexts. Strong understanding of cloud infrastructure (AWS/GCP/Azure), containers (Docker), orchestration (Kubernetes), and CI/CD practices. Experience supporting and optimizing Computer Vision workloads in real-time or batch systems. Familiarity with MLOps platforms and tools (e.g., MLflow , DVC, TensorFlow Serving, TorchServe , Airflow). Preferred Qualifications: Prior experience with model monitoring, drift detection, and retraining automation. Experience working in industries like energy, industrial equipment, manufacturing is a strong plus. Exposure to edge deployment strategies (e.g., NVIDIA Jetson, TensorRT , ONNX optimization). ITIL or SRE certifications are a bonus. Why join Genpact Be a transformation leader - Work at the cutting edge of AI, automation, and digital innovation Make an impact - Drive change for global enterprises and solve business challenges that matter Accelerate your career - Get hands-on experience, mentorship, and continuous learning opportunities Work with the best - Join 140,000+ bold thinkers and problem-solvers who push boundaries every day Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color , religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

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.,

As a Machine Learning Engineer at our company based in Coimbatore, Tamil Nadu, India, your primary responsibility will be to design, implement, and deploy machine learning models. You will work closely with data scientists to transition prototypes into production-ready systems. Managing and automating the end-to-end machine learning lifecycle will be a key part of your role. Your duties will include implementing continuous integration and continuous deployment (CI/CD) pipelines customized for machine learning workflows. Monitoring the real-time performance of deployed models, managing model drift, and executing retraining strategies will also be crucial aspects of your responsibilities. Ensuring reproducibility, traceability, and versioning for machine learning models and datasets will be essential. Additionally, you will be tasked with optimizing the machine learning infrastructure for enhanced performance, scalability, and cost-efficiency. It will be important to stay abreast of the latest trends and tools in the field of machine learning and MLOps to continuously improve our practices. To excel in this role, you will need strong programming skills, particularly in Python, along with familiarity with ML frameworks such as TensorFlow and PyTorch. Experience with data processing tools like Pandas and Scikit-learn, as well as CI/CD tools like Jenkins or GitLab CI, will be beneficial. Proficiency in containerization technologies like Docker, orchestration tools like Kubernetes, and ML model versioning tools like MLflow or DVC is also desired. Knowledge of cloud platforms such as AWS, Google Cloud, or Azure and their ML deployment services will be advantageous. The ideal candidate will have previous experience in a machine learning or data science role, along with expertise in advanced monitoring and logging tools tailored for ML models. Possessing certification or training in MLOps, machine learning, or related fields, as well as a background in software development or software engineering, will be beneficial. Familiarity with CRM & ERP systems and their data structures, along with a strong understanding of the latest machine learning trends and techniques, is highly valued. In this role, you will have the opportunity to work with a team of smart individuals in a friendly and open culture. There are no cumbersome managers or unnecessary tools to deal with, and rigid working hours are not a part of our work environment. You will have real responsibilities and the chance to expand your knowledge across various business sectors. By creating content that benefits our users on a daily basis, you will face real challenges in a rapidly evolving company environment.,

Job Summary: We are looking for a highly capable and automation-driven MLOps Engineer with 2+ years of experience in building and managing end-to-end ML infrastructure. This role focuses on operationalizing ML pipelines using tools like DVC, MLflow, Kubeflow, and Airflow, while ensuring efficient deployment, versioning, and monitoring of machine learning and Generative AI models across GPU-based cloud infrastructure (AWS/GCP). The ideal candidate will also have experience in multi-modal orchestration, model drift detection, and CI/CD for ML systems. Key Responsibilities: Develop, automate, and maintain scalable ML pipelines using tools such as Kubeflow, MLflow, Airflow, and DVC. Set up and manage CI/CD pipelines tailored to ML workflows, ensuring reliable model training, testing, and deployment. Containerize ML services using Docker and orchestrate them using Kubernetes in both development and production environments. Manage GPU infrastructure and cloud-based deployments (AWS, GCP) for high-performance training and inference. Integrate Hugging Face models and multi-modal AI systems into robust deployment frameworks. Monitor deployed models for drift, performance degradation, and inference bottlenecks, enabling continuous feedback and retraining. Ensure proper model versioning, lineage, and reproducibility for audit and compliance. Collaborate with data scientists, ML engineers, and DevOps teams to build reliable and efficient MLOps systems. Support Generative AI model deployment with scalable architecture and automation-first practices. Qualifications: 2+ years of experience in MLOps, DevOps for ML, or Machine Learning Engineering. Hands-on experience with MLflow, DVC, Kubeflow, Airflow, and CI/CD tools for ML. Proficiency in containerization and orchestration using Docker and Kubernetes. Experience with GPU infrastructure, including setup, scaling, and cost optimization on AWS or GCP. Familiarity with model monitoring, drift detection, and production-grade deployment pipelines. Good understanding of model lifecycle management, reproducibility, and compliance. Preferred Qualifications : Experience deploying Generative AI or multi-modal models in production. Knowledge of Hugging Face Transformers, model quantization, and resource-efficient inference. Familiarity with MLOps frameworks and observability stacks. Experience with security, governance, and compliance in ML environments. Location-Delhi NCR,Bangalore,Chennai,Pune,Kolkata,Ahmedabad,Mumbai,Hyderabad

We are seeking a highly experienced and technically adept Lead AI/ML Engineer to spearhead the development and deployment of cutting-edge AI solutions, with a focus on Generative AI and Natural Language Processing (NLP). The ideal candidate will be responsible for leading a high-performing team, architecting scalable ML systems, and driving innovation across AI/ML projects using modern toolchains and cloud-native technologies. Key Responsibilities Team Leadership: Lead, mentor, and manage a team of data scientists and ML engineers; drive technical excellence and foster a culture of innovation. AI/ML Solution Development: Design and deploy end-to-end machine learning and AI solutions, including Generative AI and NLP applications. Conversational AI: Build LLM-based chatbots and document intelligence tools using frameworks like LangChain , Azure OpenAI , and Hugging Face . MLOps Execution: Implement and manage the full ML lifecycle using tools such as MLFlow , DVC , and Kubeflow to ensure reproducibility, scalability, and efficient CI/CD of ML models. Cross-functional Collaboration: Partner with business and engineering stakeholders to translate requirements into impactful AI solutions. Visualization & Insights: Develop interactive dashboards and data visualizations using Streamlit , Tableau , or Power BI for presenting model results and insights. Project Management: Own delivery of projects with clear milestones, timelines, and communication of progress and risks to stakeholders. Required Skills & Qualifications Languages & Frameworks: Proficient in Python and frameworks like TensorFlow , PyTorch , Keras , FastAPI , Django NLP & Generative AI: Hands-on experience with BERT , LLaMA , Spacy , LangChain , Hugging Face , and other LLM-based technologies MLOps Tools: Experience with MLFlow , Kubeflow , DVC , ClearML for managing ML pipelines and experiment tracking Visualization: Strong in building visualizations and apps using Power BI , Tableau , Streamlit Cloud & DevOps: Expertise with Azure ML , Azure OpenAI , Docker , Jenkins , GitHub Actions Databases & Data Engineering: Proficient with SQL/NoSQL databases and handling large-scale datasets efficiently Preferred Qualifications Masters or PhD in Computer Science, AI/ML, Data Science, or related field Experience working in agile product development environments Strong communication and presentation skills with technical and non-technical stakeholders

We are looking for Indias top 1% Computer Vision Engineers for a unique job opportunity to work with the industry leaders Who can be a part of the community? We are looking for top-tier Computer Vision (CV) Engineers with expertise in image/video processing, object detection, and generative AI If you have experience in this field then this is your chance to collaborate with industry leaders Whats in it for you? Pay above market standards The role is going to be contract based with project timelines from 2 12 months, or freelancing Be a part of an Elite Community of professionals who can solve complex AI challenges Work location could be: Remote (Highly likely) Onsite on client location Deccan AIs Office: Hyderabad or Bangalore Responsibilities: Develop and optimize computer vision models for tasks like object detection, image segmentation, and multi-object tracking Lead research on novel techniques using deep learning frameworks (TensorFlow, PyTorch, JAX) Build efficient computer vision pipelines and optimize models for real-time performance Deploy models using microservices (Docker, Kubernetes) and cloud platforms (AWS, GCP, Azure) Lead MLOps practices, including CI/CD pipelines, model versioning, and training optimizations Required Skills: Expert in Python, OpenCV, NumPy, and deep learning architectures (eg, ViTs, YOLO, Mask R-CNN) Strong knowledge in computer vision fundamentals, including feature extraction and multi-view geometry with experience in deploying and optimizing models with TensorRT, Open VINO, and cloud/edge solutions Proficient with MLOps tools (ML flow, DVC), CI/CD, and distributed training frameworks Experience in 3D vision, AR/VR, or LiDAR processing is a plus Nice to Have: Experience with multi-camera vision systems, LiDAR, sensor fusion, and reinforcement learning for vision tasks Exposure to generative AI models (eg, Stable Diffusion, GANs) and large-scale image processing (Apache Spark, Dask) Research publications or patents in computer vision and deep learning Location-Delhi NCR,Bangalore,Chennai,Pune,Kolkata,Ahmedabad,Mumbai,Hyderabad

Job Requirements Education: Bachelors degree (Statistics, Business Analytics, Data Science, Math, Economics, etc.) Masters degree preferred (MBA/MS/M.Tech in Computer Science or related field) Experience: 5–7 years in a Data Science/Advanced Analytics role Behavioral Skills: Delivery Excellence Business Orientation Social Intelligence Innovation and Agility Knowledge & Technical Skills: Functional analytics experience (Supply Chain, Marketing, Customer Analytics, etc.) Statistical modeling using tools such as R, Python, KNIME Knowledge of statistics and experimental design (A/B testing, hypothesis testing, causal inference) Experience building and evaluating machine learning models MLOps tools and practices (MLflow, DVC, Docker, etc.) Strong Python programming (Pandas, Scikit-learn, PyTorch/TensorFlow, etc.) Experience with big data technologies (AWS, Azure, GCP, Hadoop, Spark) Familiarity with relational (MySQL, SQL Server) and non-relational (MongoDB, DynamoDB) databases BI and reporting tools (Power BI, Tableau, Alteryx) Proficiency with Microsoft Office applications (especially Excel) Roles & Responsibilities Analytics & Strategy: Analyze large-scale structured and unstructured data to develop insights and machine learning models across various business domains Apply statistical and machine learning techniques to generate value from operational, financial, and customer data Recommend best-fit algorithms and models with clear justifications for business use Leverage cloud platforms for modeling and big data analysis; utilize data visualization tools to communicate results Operational Excellence: Follow industry-standard coding practices and development lifecycles Formulate hypotheses, develop analytics frameworks, and bring structure to complex problems Collaborate with Data Engineering to maintain core data infrastructure and automate analytical processes Stakeholder Engagement: Work cross-functionally with business stakeholders, engineers, and visualization experts to deliver impactful projects Communicate complex models and results to non-technical stakeholders in a clear and compelling way