Senior ML Operations Engineer

. Designs, builds, and maintains scalable ML infrastructure and pipelines for model training, deployment, and monitoring .

Posted 5/5/2026full-timeSan Francisco • California, Illinois • 🇺🇸 United StatesSenior💰 $118,000 - $203,000 per yearWebsite

Tools & technologies

AWSDockerKubernetesPython

Key responsibilities & impact

Designs, builds, and maintains scalable ML infrastructure and pipelines for model training, deployment, and monitoring
Optimizes orchestration processes to ensure efficient deployment and management of predictive models
Optimizes resource usage to minimize infrastructure expense while maximizing performance
Monitors and maintains the performance, security, and scalability of the ML infrastructure
Collaborates with data scientists and software engineers to streamline the ML lifecycle from development to production
Develops and maintains tools for data analysis, experimentation, model versioning, and artifact management
Supports data and model governance requirements as needed
Creates robust monitoring systems to measure and trend model performance, detect model drift, and ensure optimal performance of models in production
Develops automation scripts and tools to improve the efficiency and reliability of MLOps processes
Optimizes ML workflows for efficiency, scalability, and reliability
Provides technical assistance and mentorship to all team members; troubleshoots complex issues and escalates issues, as necessary
Supports the company commitment to risk management and protecting the integrity and confidentiality of systems and data

What you’ll need

Education and experience typically obtained through completion of a Bachelor's degree in Computer Science, Engineering, or a related field
Minimum 5 years’ experience in Data Science, ML Engineering or ML Ops capacity
Strong programming skills in Python and experience with Data Science and ML packages and frameworks
Experience with AWS services
Proficiency with containerization technologies (Docker, Kubernetes) and CI/CD practices
Experience deploying models with MLOps tools such as MLflow, Kubeflow, or similar platforms
Expert understanding of data management, distributed computing, and software architecture principles
Proven experience delivering real-time models in production environments
Background and drug screen

Comp & perks

Healthcare Coverage – Competitive medical (PPO/HDHP), dental, and vision plans
401(k) Retirement Plan – Featuring a 100% Company Safe Harbor Match on your first 6% deferral immediately upon eligibility
Paid Time Off – Flexible Time Off for Exempt (salaried) employees, as well as generous PTO for Non-Exempt (hourly) employees, plus 11 paid company holidays and a paid volunteer day
12 weeks of Paid Parental Leave
Maven Family Planning – provides support through your Parenting journey including egg freezing, fertility, adoption, surrogacy, pregnancy, postpartum, early pediatrics, and returning to work

ATS Keywords

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Hard Skills & Tools

PythonData ScienceMachine LearningMLOpsAWSDockerKubernetesCI/CDMLflowKubeflow

Soft Skills

collaborationmentorshiptroubleshootingrisk management