Hybrid Senior ML Ops Engineer

at EEOC

• Job title: Senior ML Ops Engineer
• Job type: Full Time
• Experience level: Senior
• Salary: $115,000 - $145,000 per year
• Degree requirement: Bachelor's Degree
• Tech skills: AWS, Docker, Kubernetes, Python
• Location requirements: Hybrid, San Francisco, United States

About the role

• Senior ML Ops Engineer at Early Warning designing infrastructure for machine learning models. Collaborating across teams to enhance model deployment and performance in financial systems.

Responsibilities

• 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.

Requirements

• 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.

Benefits

• Healthcare Coverage – Competitive medical (PPO/HDHP), dental, and vision plans as well as company contributions to your Health Savings Account (HSA) or pre-tax savings through flexible spending accounts (FSA) for commuting, health & dependent care expenses.
• 401(k) Retirement Plan – Featuring a 100% Company Safe Harbor Match on your first 6% deferral immediately upon eligibility.
• Paid Time Off – Unlimited 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.
• And SO much more!