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

- Strong 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 workplace.

Machine Learning

📌 LEAD ENGINEER - Machine Learning (Pune)
🏢 Happiest Minds Technologies
📍 Pune