Responsibilities

Design, implement, and maintain MLOps pipelines for deploying machine learning models.
Collaborate with data scientists to understand model requirements and translate them into production-ready solutions.
Monitor and optimize the performance of machine learning models in production.
Develop and maintain documentation for MLOps processes and workflows.
Implement CI/CD practices for machine learning projects.
Ensure compliance with data governance and security policies.
Provide technical support and troubleshooting for deployed models.
Stay updated with the latest trends and technologies in MLOps and machine learning.

Mandatory Skills

Robust knowledge of machine learning concepts and algorithms.
Experience with MLOps tools and frameworks (e.g., MLflow, Kubeflow, TFX).




Proficiency in programming languages such as Python and R.
Familiarity with cloud platforms (e.g., AWS, Azure, GCP) and their ML services.
Experience with containerization technologies (e.g., Docker, Kubernetes).
Strong understanding of CI/CD processes and tools (e.g., Jenkins, GitLab CI).
Knowledge of data preprocessing, feature engineering, and model evaluation techniques.

Preferred Skills

Experience with big data technologies (e.g., Hadoop, Spark).
Familiarity with data visualization tools (e.g., Tableau, Power BI).
Knowledge of DevOps practices and tools.
Experience in working with cross-functional teams in an Agile environment.

Machine Learning

📌 LEAD ENGINEER (Pune)
🏢 Happiest Minds Technologies
📍 Pune