Lead AI/ML Engineer Cynosure Corporate Solutions

10.0 - 15.0 years

35 - 40 Lacs

chennai

Work from Office

Key Responsibilities: Leadthedesign, development, and implementation of AI/ML models and solutions. Mentorandguide a team of AI/ML engineers, fostering a collaborative and innovative environment. Translate business requirements into technical specifications and tasks. Research and evaluate new AI/ML technologies and methodologies, including Large and Small Language Models and Agentic AI frameworks. Implement and optimize AI/ML pipelines on cloud platforms such as Azure and AWS. Ensurethe quality, performance, and scalability of AI/ML solutions. Collaborate with cross-functional teams, including product, engineering, and business stakeholders. Contribute to the development of best practices and standards for AI/ML development. Maintain up-to-date knowledge of the latest advancements in AI/ML and related fields. Skills&Experience Master's degree or Bachelor's degree in Computer Science or Information Technology 8+ years of professional experience in Machine Learning, Software Engineering, and Data Science Solid understanding of generative models, including Large and Small Language Models. Experience implementing Agentic AI using LLM/SLM orchestration. Proficiency in classical data science methodologies (statistical, prescriptive, and predictive analytics). Experience in software design and practical understanding of modern AI/ML software components (data, data warehousing, AI/ML tools, inference, and microservices). Practical knowledge of cloud platforms and AI/ML tools like Azure ML and AWS SageMaker

Posted 5 days ago

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ML Ops Engineer VirtueVin Solutions

4.0 - 8.0 years

0 Lacs

chennai, tamil nadu

On-site

As a skilled MLOps Support Engineer, you will be responsible for monitoring and managing ML model operational pipelines in AzureML and MLflow. Your primary focus will be on automation, integration validation, and CI/CD pipeline management to ensure stability and reliability in model deployment lifecycles. Your objectives in this role include supporting and monitoring MLOps pipelines in AzureML and MLflow, managing CI/CD pipelines for model deployment and updates, handling model registry processes, performing testing and validation of integrated endpoints, automating monitoring and upkeep of ML pipelines, as well as troubleshooting and resolving pipeline and integration-related issues. In your day-to-day responsibilities, you will support production ML pipelines using AzureML and MLflow, configure and manage model versioning and registry lifecycle, automate alerts, monitoring tasks, and routine pipeline operations, validate REST API endpoints for ML models, implement CI/CD workflows for ML deployments, document and troubleshoot operational issues related to ML services, and collaborate with data scientists and platform teams to ensure delivery continuity. To excel in this role, you should possess proficiency in AzureML, MLflow, and Databricks, have a strong command over Python, experience with Azure CLI and scripting, a good understanding of CI/CD practices in MLOps, knowledge of model registry management and deployment validation, and at least 3-5 years of relevant experience in MLOps environments. While not mandatory, it would be beneficial to have skills such as exposure to monitoring tools like Azure Monitor and Prometheus, experience with REST API testing tools such as Postman, and familiarity with Docker/Kubernetes in ML deployments.,

Posted 1 month ago

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Data engineer Lead- Python Azure Optum

7.0 - 12.0 years

18 - 27 Lacs

hyderabad

Hybrid

Description - External Key Responsibilities: Develop and deploy data pipelines and machine learning models on cloud platforms (Azure, Databricks, AzureML). Utilize Python and its libraries (scikit-learn, Pandas, NumPy, TensorFlow, PyTorch) for data processing and model development. Implement and manage RAG modeling using vector databases (Milvus, Chroma, FAISS). Monitor and maintain the health and performance of deployed ML models using model observability tools. Design, build, and optimize AI models and generative AI applications. Create and fine-tune prompts for generative AI systems, including zero-shot, few-shot, and chain-of-thought approaches. Ensure the scalability, reliability, and efficiency of AI/ML solutions in production environments. Conduct exploratory data analysis (EDA) to extract meaningful insights and prepare data for modeling. Apply MLOps practices to streamline model deployment and management. Build and maintain CI/CD pipelines (Terraform). Ensure proper versioning of models and data using tools like MLFlow, Delta Lake, DVC, and LakeFS. Qualifications - External Required Skills: Proficiency in Python and its libraries (scikit-learn, Pandas, NumPy, TensorFlow, PyTorch). Experience with cloud platforms (Azure, Databricks , AzureML). Knowledge of Lang Chain and RAG modeling with vector databases (like Milvus, Chroma, FAISS). Understanding of deep learning, particularly in NLP . Familiarity with model observability tools for tracking, alerting, and compliance monitoring. Strong MLOps skills. Experience with model versioning tools (MLFlow) and data versioning tools (Delta Lake, DVC, LakeFS). Ability to build and maintain CI/CD pipelines. Preferred Qualifications: Strong problem-solving skills and attention to detail. Excellent communication and teamwork abilities. Proven track record of working on AI/ML projects.

Posted Date not available

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