Senior MLOps Engineer
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Job Description
Senior MLOps Engineer leading the design, deployment, and scaling of machine learning systems. Collaborating to enable faster and high-quality ML workflows while ensuring reliable ML pipelines.
Responsibilities:
- Design, build, and maintain scalable ML pipelines for training, testing, and deployment
- Deploy & maintain machine learning models and ensure their performance, reliability, and monitoring
- Collaborate with data scientists and engineers to streamline experimentation and deployment workflows
- Implement CI/CD practices for ML systems (ML CI/CD)
- Manage and optimize cloud-based infrastructure for ML workloads
- Develop monitoring, logging, and alerting systems for model performance and data drift
- Ensure reproducibility, versioning, and governance of ML models and datasets
- Advocate for best practices in MLOps, DevOps, and software engineering
Requirements:
- 5+ years of experience in software engineering, DevOps, or MLOps roles
- Strong programming skills in Python (and familiarity with Java/Go is a plus)
- Experience with ML frameworks such as TensorFlow, PyTorch, or similar
- Hands-on experience with containerization and orchestration tools (Docker, Kubernetes)
- Experience with cloud platforms (AWS, GCP, or Azure)
- Familiarity with CI/CD tools (e.g., GitHub Actions, Jenkins, GitLab CI)
- Strong understanding of data pipelines, distributed systems, and API development
- Experience with monitoring tools and logging frameworks
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