Build and maintain end-to-end ML pipelines for data ingestion, feature computation, model training, validation, deployment, and inference, all at substantial scale of data
Stand up and manage a feature store, ensuring feature consistency, lineage, and reuse across teams.
Expertise with best in class tools for managing deployment, scheduling, and environments and how to use them in the specialized regime of ML Infrastructure.
Develop automated model deployment workflows with CI/CD, safe rollout strategies, and reproducibility guarantees.
Implement monitoring and observability for ML systems, including data quality checks, drift detection, performance metrics, and alerting.
Build and support training environments with experiment tracking, distributed training, hyperparameter tuning, and artifact and environment management.
Collaborate with ML engineers and data engineers to streamline workflows, improve model iteration speed, and enforce MLOps best practices.
Ensure reliability, scalability, and maintainability of ML systems through strong engineering and operational rigor.

Bachelor’s degree in CS, Engineering, Mathematics, or related field.
5+ years experience in MLOps, ML platform engineering, ML infrastructure, or similar roles.
Strong experience building production ML pipelines and supporting end-to-end ML workflows.
Excellent engineering fundamentals: Python, SQL, bash, Git.
Experience with big data and distributed compute: Snowflake, Spark/pySpark, Airflow, Kubernetes, Docker, Helm.
Experience with ML frameworks (PyTorch, TensorFlow) sufficient to support training pipelines and deployment workflows.
Strong understanding of cloud platforms (AWS, GCP, or Azure).
Ability to produce well-engineered, maintainable software with tests, documentation, and operational rigor.
Experience with data quality frameworks, observability tooling, or experiment tracking systems.

Health, Dental & Vision Full premium coverage for you. Partial coverage for dependents.
Family Formation Up to $200,000 in fertility and family-building support, covering IVF, surrogacy, egg freezing, and adoption.
Retirement: 401(k) with 6% match and immediate vesting.
Compensation: Industry-competitive compensation, company bonus, and equity for every employee.
Gender-Affirming Care : Industry-leading gender-affirming offerings with up to 90% cost coverage, access to Included Health, monthly stipends for HRT, and more.
Time Off & Rest Flexible vacation policy. Two company-wide rest weeks per year.
Other Benefits: Monthly stipends for cell phone, internet, wellness, food, and commuting, breakfast/lunch

Staff MLOps Engineer

Key skills