Senior ML Operations (MLOps) Engineer

About the role

A Senior MLOps Engineer will be responsible for overseeing the end-to-end lifecycle of machine learning models, from development through deployment. This includes managing infrastructure, automating workflows, and ensuring model quality and reliability.

Responsibilities

• Develop and maintain CI/CD pipelines for machine learning models
• Optimize and automate model training and inference processes
• Collaborate with data scientists to integrate machine learning models into production systems
• Ensure compliance with regulatory standards and best practices in MLOps
• Monitor and troubleshoot model performance and infrastructure issues
• Document and communicate technical decisions and processes to non-technical stakeholders

Requirements

• Bachelor's degree in Computer Science, Engineering, Statistics, or a related field
• 5+ years of experience in machine learning, software engineering, or a related field
• Experience with cloud platforms (AWS, Google Cloud, Azure)
• Hands-on experience with MLOps tools and frameworks (e.g., Kubeflow, MLflow, Docker)
• Strong understanding of data pipelines, model deployment, and monitoring
• Excellent problem-solving and debugging skills
• Ability to work independently and manage multiple projects simultaneously

Qualifications

• Experience with Kubernetes and container orchestration
• Knowledge of deep learning frameworks (TensorFlow, PyTorch, etc.)
• Experience with version control systems (Git)
• Understanding of data privacy and security principles

Skills

• Python programming
• Experience with SQL and NoSQL databases
• Good communication and collaboration skills

Benefits

• Flexible remote work options
• Competitive salary commensurate with experience
• Health insurance benefits
• 401(k) retirement plan
• Professional development opportunities

Pay

• Base salary range: $120,000 - $180,000 annually

Schedule

• Full-time position