MLOps Engineer
Experience: 5–7 Years
Location: Hyderabad
Work Mode: Work From Office (5 Days/Week)
Key Responsibilities
- Assist in the design and development of MLOps pipelines for deployment and integration of ML models.
- Support data scientists and senior engineers in operationalizing machine learning models.
- Automate model training, testing, and deployment workflows using Python and shell scripting.
- Monitor models in production and flag performance issues or anomalies for resolution.
- Implement and maintain version control practices for ML models and data.
- Containerize ML services and applications using Docker.
- Set up and maintain Jenkins pipelines for continuous integration and delivery.
- Support Kubernetes-based deployment of ML workloads.
- Ensure adherence to security, data privacy, and governance standards.
- Document MLOps processes, workflows, and configurations for team knowledge sharing.
- Stay current with emerging MLOps tools, frameworks, and best practices.
- Participate in sprint planning, standups, and retrospectives in an Agile environment.
Skills
- Hands-on experience or strong familiarity with MLFlow.
- Proficiency in Python; experience with automation and Shell/Bash scripting.
- Working knowledge of Docker for containerization.
- Experience with Jenkins or similar CI/CD tools.
- Basic understanding of Kubernetes for container orchestration.
- Understanding of machine learning concepts and the model development lifecycle.
- Familiarity with SDLC practices and Agile methodologies.
- Good analytical and problem-solving skills.
- Strong communication skills and ability to work collaboratively in a team.
- Bachelor's degree in Computer Science, Data Science, Information Technology, or a related field.
