ML Ops Lead

Location: Bangalore/Hyderabad

Work Type: Hybrid

The Role:

• Collaborate with data scientists and ML engineers throughout the ML lifecycle, from model development to production deployment.
• Design and implement MLOps pipelines using tools and frameworks like TensorFlow Serving, Kubeflow, MLflow, or similar solutions.
• Design, develop, and implement data pipelines and engineering infrastructure to support enterprise-scale machine learning systems. This could involve tasks such as data ingestion, pre-processing, transformation, feature engineering, and model training.
• Design and implement cloud-based MLOps solutions using platforms like Azure ML, Azure Databricks, AWS SageMaker, or Google Cloud AI Platform.
• Hands-on experience with Azure cloud services, including Azure ML, Azure DevOps, AKS, Azure Container Registry (ACR), Azure Application Insights, and Azure Log Analytics, is essential.
• Experience in containerization technologies like Docker and Kubernetes is a plus.
• Experience deploying and maintaining various types of machine learning models in production, including text/NLP models, is required.
• Experience with Generative AI (GenAI) projects is a plus.
• Build CI/CD pipelines using tools like GitLab CI, GitHub Actions, Airflow, or similar solutions to automate the ML lifecycle.
• Perform data science model reviews, including code refactoring and optimization, containerization, deployment, versioning, and monitoring of the model’s quality.
• Support data model development, with a focus on auditability, versioning, and data security. This could involve implementing practices like lineage tracking, model explainability, and bias detection.
• Mentoring junior MLOps engineers or collaborating with multiple teams like consulting, data engineering, development team.

Qualifications:

• Total 7+ years of work experience , 3+ years in MLOps
• Strong expertise in GenAI, advanced NLP, computer vision, and ML techniques.
• Experience in designing, developing, and deploying production-grade AI solutions.
• Excellent communication and collaboration skills. Ability to work independently and as part of a team.
• Strong problem-solving and analytical skills.
• Stay up-to-date on the latest advancements in MLOps technologies and identify and evaluate new tools and techniques to improve the performance, maintainability, and reliability of machine learning systems.

We offer you

• Opportunity to work on cutting-edge AI projects
• A chance to try things, take risks.
• Meaningful problems you’ll be proud of solving, which directly adds to your career growth & skill development
• People you will be comfortable working with