Senior MLOps Engineer

Job Description

We are seeking a Senior MLOps Engineer to design, develop, and maintain scalable Machine Learning (ML) pipelines for training, testing, and deployment. The role involves deploying and maintaining machine learning models, ensuring performance, reliability, and monitoring. You will also collaborate with data scientists and engineers to streamline experimentation and deployment workflows, implement CI/CD practices for ML systems (ML CI/CD), and manage and optimize cloud-based infrastructure for ML workloads. Furthermore, you'll develop monitoring, logging, and alerting systems for model performance and data drift. You'll be responsible for ensuring reproducibility, versioning, and governance of ML models and datasets, as well as advocating for best practices in MLOps, DevOps, and software engineering.

Qualifications

1. 5+ years of experience in software engineering, DevOps, or MLOps roles. 2. Strong programming skills in Python; familiarity with Java/Go is a plus. 3. Experience with ML frameworks such as TensorFlow, PyTorch, or similar. 4. Hands-on experience with containerization and orchestration tools (Docker, Kubernetes). 5. Experience with cloud platforms (AWS, GCP, or Azure). 6. Familiarity with CI/CD tools (e.g., GitHub Actions, Jenkins, GitLab CI). 7. Strong understanding of data pipelines, distributed systems, and API development. 8. Experience with monitoring tools and logging frameworks.