Sr. Machine Learning Engineer

Unity Technologies SF is seeking a Sr. Machine Learning Engineer to build and operate the ML Engineering Infrastructure platform. This role covers the full path from data and feature pipelines through distributed training, workflow orchestration, serving, and observability, working closely with partners to move production ML models reliably from training into deployment.

Responsibilities

• Build and maintain data and feature pipelines that produce training datasets for machine learning models and experimentation.
• Develop and improve infrastructure for distributed training workflows.
• Build and operate multi-stage ML pipelines using workflow orchestration tools.
• Contribute to model serving and deployment infrastructure to support reliable movement from training to production.
• Strengthen reproducibility and reliability across the stack through monitoring, alerting, dataset validation, and testing.
• Own end-to-end projects scoped with a manager, driving work from design through rollout using independent judgment.
• Investigate uncommon or inconsistent issues across pipelines and training systems, identify underlying patterns, and translate them into concrete improvements.
• Balance hands-on execution with long-term platform direction, delivering immediate outcomes while moving the infrastructure forward.
• Partner with ML engineers, researchers, and peers across teams, sharing progress and tradeoffs with managers and directors.
• Adopt new tools and parts of the stack as team priorities evolve.

Requirements

• Experience building ML infrastructure, data platforms, or distributed systems in production.
• Strong Python skills and experience working with data-intensive workloads.
• Hands-on experience with ML frameworks such as PyTorch and distributed compute such as Ray or Spark.
• Experience with data pipelines, model training workflows, or large datasets beyond academic settings.
• Comfort working across multiple layers of the ML stack, with a track record of learning new tools and systems quickly.
• Ability to identify patterns in ambiguous or inconsistent problems and turn them into practical technical needs.
• Clear communication and a collaborative approach 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

Location and Salary

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

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 like Airflow or Prefect
• Experience with model serving frameworks such as Triton, KServe, or Ray Serve
• Exposure to large-scale data platforms (data lakes, warehouses, streaming systems such as Kafka)
• Familiarity with feature stores or experimentation platforms