Sr. Machine Learning Engineer

Join Unity Technologies SF to build and operate the Machine Learning Engineering Infrastructure platform that moves production ML models from training to serving.

Responsibilities

• Build and maintain data and feature pipelines that produce training datasets for ML models and experimentation
• Develop and continuously improve distributed training infrastructure and workflows
• Design, build, and run multi-stage ML pipelines using workflow orchestration tools
• Contribute to model serving and deployment infrastructure to support reliable promotion of models into production
• Increase reproducibility and reliability with monitoring, alerting, dataset validation, and testing
• Own end-to-end projects scoped with your manager, from design through rollout, applying judgment as needed
• Investigate uncommon or inconsistent failures across pipelines and training systems, identify the underlying patterns, and drive concrete improvements
• Balance hands-on execution with platform direction by delivering immediate needs while moving the system forward
• Partner with ML engineers, researchers, and cross-team peers; share progress and tradeoffs with managers and directors
• Adopt new tools and expand into unfamiliar parts of the stack as team priorities evolve

Requirements

• Production experience building ML infrastructure, data platforms, or distributed systems
• Strong Python skills with experience working on data-intensive workloads
• Hands-on experience with ML frameworks such as PyTorch and distributed compute such as Ray or Spark
• Experience with data pipelines and model training workflows, including work with large datasets beyond academic settings
• Comfort working across multiple layers of the ML stack and learning new systems quickly
• Ability to recognize patterns in ambiguous or inconsistent issues and translate them into actionable technical needs
• Clear communication and collaboration with peers, managers, and partner teams
• Bachelor’s degree in Computer Science, Machine Learning, Systems, or a related field, or equivalent practical experience

Technologies

• Python
• PyTorch
• Ray
• Spark
• Kubernetes
• GCP
• AWS
• Prometheus
• Grafana
• Airflow
• Prefect
• Triton
• KServe
• Ray Serve
• Kafka

Benefits

• Comprehensive health, life, and disability insurance
• Commute subsidy
• Employee stock ownership
• Competitive retirement/pension plans
• Generous vacation and personal days
• Support for new parents through leave and family-care programs
• Office food snacks
• Mental Health and Wellbeing programs and support
• Employee Resource Groups
• Global Employee Assistance Program
• Training and development programs
• Volunteering and donation matching program

Nice to Have

• Experience with Kubernetes and cloud infrastructure (GCP or AWS)
• Experience with observability tooling such as Prometheus and Grafana
• Experience with workflow orchestration systems (Airflow, Prefect, etc.)
• Experience with model serving frameworks such as Triton, KServe, or Ray Serve
• Exposure to large-scale data platforms (data lakes, warehouses, and streaming systems such as Kafka)
• Familiarity with feature stores or experimentation platforms

Location: Bellevue, WA (onsite). Compensation: USD 140,700 - 232,300 per year.