Senior ML Engineer: Scalable ML Infra & Pipelines (Onsite)

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 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.