Senior MLOps Engineer

Design, build, and scale robust machine learning infrastructure for advanced AI systems as a Senior MLOps Engineer.

Requirements

• 6–10+ years of experience in software or ML engineering, with at least 3+ years in MLOps or ML infrastructure.
• Strong proficiency in Python, C, C++, Bash, or similar programming languages.
• Proven experience deploying and managing ML models in production environments.
• Expertise with Docker, Kubernetes, and scalable ML system design.
• Experience with cloud platforms such as AWS, GCP, or Azure and GPU orchestration.
• Hands-on knowledge of CI/CD pipelines (GitHub Actions, Jenkins, or similar).
• Familiarity with MLflow, Weights & Biases, Kubeflow, or other experiment tracking and pipeline automation tools.
• Solid understanding of data versioning, model reproducibility, and monitoring strategies.
• Excellent problem-solving skills and a collaborative, team-oriented mindset.

Benefits

• Competitive base salary range: $190,000–$230,000 annually, based on skills and experience.
• Fully remote work with occasional travel 1–2 times per year for company-wide or departmental meetings.
• Comprehensive health, dental, vision, life, and disability insurance.
• Generous paid time off and company holidays.
• Flexible work environment and opportunities for professional growth.