Staff ML Infrastructure Engineer: Large-Scale Pipelines

Unity Technologies; Bellevue (WA); On-site; USD 210,000 - 284,000; Full time

Benefits offered by this job

Health insurance

Employee stock ownership

Generous vacation

Job summary

Unity Technologies in Bellevue, WA is seeking a Staff ML Engineer to design and evolve the large-scale offline ML platform. You will own data pipelines for training datasets, orchestrate ML workflows, and enable distributed model training across multi-node systems.

Collaborate with ML engineers and platform teams to ensure reliability, scalability, and cost efficiency, while shaping how datasets are prepared and models trained, validated, and delivered to distributed training environments.

Qualifications

• Experience building large-scale ML pipelines.
• Experience with distributed computing frameworks like Ray, Spark, Flink; familiarity with Ray ecosystem.
• Experience building infrastructure for training data generation, dataset prep, or ML feature pipelines.
• Deep experience designing and operating production-grade data pipelines.
• Strong Python programming and handling large-scale distributed workloads.
• Experience with data lakes, warehouses, orchestration systems, and streaming platforms.
• Strong systems thinking on performance, scalability, reliability, and cost.
• Proven ability to lead technical direction across teams without formal authority.

Responsibilities

• Design and operate large-scale data pipelines that generate training datasets.
• Develop infrastructure supporting distributed training workflows using PyTorch, Ray Data, Ray Train.
• Integrate ML pipelines with Flyte, Airflow, or similar for multi-stage training.
• Improve reproducibility and observability of ML pipelines via validation and testing.
• Optimize resource utilization across distributed compute systems.
• Partner with ML engineers to enable large-scale experimentation and model iteration.
• Lead architectural improvements for scalable, reliable offline ML pipelines.

Skills

Large-scale ML pipelines

Distributed computing

Python programming

Data infrastructure

System design & scalability

Leadership without authority

Performance & cost tradeoffs

Tools

Ray Data

Ray Train

Flyte

Airflow

Spark

Flink

Job description

Unity Technologies in Bellevue, WA is seeking a Staff ML Engineer to design and evolve the large-scale offline ML platform. You will own data pipelines for training datasets, orchestrate ML workflows, and enable distributed model training across multi-node systems.

Collaborate with ML engineers and platform teams to ensure reliability, scalability, and cost efficiency, while shaping how datasets are prepared and models trained, validated, and delivered to distributed training environments.