Sr. Machine Learning Engineer

Unity Technologies SF; Bellevue (WA); On-site; USD 141,000 - 232,000; Full time

Benefits offered by this job

Health insurance

Commuter subsidy

Employee stock ownership

Retirement plans

Generous vacation

Job summary

Unity Technologies SF is building an ML Engineering Infrastructure platform that helps teams move production machine learning reliably from training into deployed services.

As a Senior Machine Learning Engineer, you will work across data and feature pipelines, distributed training, workflow orchestration, serving, and observability, partnering with ML engineers and researchers to improve end-to-end reliability.

Qualifications

• Experience building ML infrastructure, data platforms, or distributed systems in production.
• Strong Python skills and experience 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 and a record of learning new tools and systems quickly.
• Ability to recognize patterns in ambiguous or inconsistent problems and translate 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 related field, or equivalent practical experience.

Responsibilities

• Build and maintain data and feature pipelines that produce training datasets for model development and experimentation.
• Develop and improve infrastructure for distributed training workflows.
• Create and run multi-stage ML pipelines using workflow orchestration tools.
• Contribute to model serving and deployment infrastructure for reliable transitions from training to production.
• Strengthen reproducibility and reliability through monitoring, alerting, dataset validation, and testing across the stack.
• Own scoped projects from design through rollout with independent judgment.
• Investigate pipeline issues and implement concrete improvements.
• Balance hands-on execution with broader platform direction.

Skills

Python

PyTorch

Ray

Spark

Data pipelines

Communication

Problem solving

Bachelor's degree

Education

Bachelor’s degree in CS/ML/Systems

Tools

Kubernetes

GCP

AWS

Prometheus

Grafana

Airflow

Prefect

Triton

KServe

Ray Serve

Kafka

Job description

Unity Technologies SF is building and operating an ML Engineering Infrastructure platform that helps teams move production machine learning reliably from training into deployed services. As a Senior Machine Learning Engineer, you will work across data and feature pipelines, distributed training, workflow orchestration, serving, and observability, partnering with ML engineers and researchers to improve end-to-end reliability.

What you’ll do

• Build and maintain data and feature pipelines that produce training datasets for model development and experimentation
• Develop and continuously improve infrastructure for distributed training workflows
• Create and run multi-stage ML pipelines using workflow orchestration tools
• Contribute to model serving and deployment infrastructure to support dependable transitions from training to production
• Strengthen reproducibility and reliability through monitoring, alerting, dataset validation, and testing across the stack
• Own scoped projects with your manager, carrying them from design through rollout using independent judgment
• Investigate uncommon or inconsistent issues across pipelines and training systems, identify underlying patterns, and implement concrete improvements
• Balance hands‑on execution with broader platform direction, delivering on near‑term needs while advancing the platform
• Partner with ML engineers, researchers, and teams across the organization, sharing progress and tradeoffs with managers and directors
• Adopt new tools and parts of the stack as team priorities evolve

Required skills and experience

• Experience building ML infrastructure, data platforms, or distributed systems in production
• Strong Python skills and experience 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 and a record of learning new tools and systems quickly
• Ability to recognize patterns in ambiguous or inconsistent problems and translate 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

Tools you may work with

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

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