Sr. Machine Learning Engineer

Unity’s ML Engineering Infrastructure team is hiring a Sr. Machine Learning Engineer to build and operate the platform that powers product intelligence and production ML models.

Responsibilities

• Build and maintain data and feature pipelines to create training datasets for machine learning models and experimentation
• Develop and enhance infrastructure for distributed training workflows
• Implement and run multi-stage ML pipelines using workflow orchestration tools
• Contribute to model serving and deployment infrastructure to move models reliably from training to production
• Strengthen reproducibility and reliability via monitoring, alerting, dataset validation, and testing
• Own scoped projects from design through rollout, applying judgment throughout delivery
• Investigate uncommon or inconsistent issues in pipelines and training systems, identify the underlying patterns, and translate them into concrete improvements
• Balance hands-on execution with long-term platform direction, addressing near-term needs while progressing the stack
• Partner across ML engineering, research, and other teams; share progress, tradeoffs, and outcomes with managers and directors
• Adopt new tools and areas of the stack as team priorities shift

Requirements

• Production experience building ML infrastructure, data platforms, or distributed systems
• Strong Python skills and experience with data-intensive workloads
• Hands-on experience with ML frameworks (e.g., PyTorch) and distributed compute (e.g., Ray, Spark)
• Experience with data pipelines, model training workflows, or large datasets beyond academic settings
• Ability to operate across multiple layers of the ML stack, with a track record of learning new systems quickly
• Skill in recognizing patterns in ambiguous or inconsistent issues and turning 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

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

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

Location: Mountain View, CA (onsite)

Base salary: USD 140,700 - 232,300 per yearly

Compensation details: Zone A: $178,700 - $232,300. Zone B: $159,100 - $206,800. Zone C: $140,700 - $182,900. Beyond base salary, the role may be eligible for equity awards and participation in company incentive plans (such as annual discretionary bonuses or sales commissions). Final offer depends on geographic location and the candidate’s relevant experience, professional background, and skill set.