ML Systems Engineer, Offline Infrastructure & Pipelines

Unity Technologies; Mountain View (CA); On-site; USD 117,000 - 152,000; Full time

Benefits offered by this job

Comprehensive health insurance

Commute subsidy

Employee stock ownership

Competitive retirement/pension plans

Generous vacation and personal days

Support for new parents through leave

Job summary

Unity Technologies seeks a Machine Learning Engineer to join the Offline Infrastructure team, focusing on large-scale data pipelines and distributed model training. You will help generate training datasets, support multi-stage ML workflows, and collaborate with researchers to translate ideas into scalable systems.

The role blends research and production, offering exposure to PyTorch, Spark, and orchestration tools. Strong Python skills and a passion for reliable ML infrastructure are required.

Qualifications

• Bachelor's degree in CS, ML, Systems or related field.
• Strong background in ML systems, distributed systems, or large-scale data processing.
• Experience with Python and data-intensive workloads.
• Familiarity with ML frameworks (PyTorch, TensorFlow) and distributed systems (Ray, Spark).
• Experience with data pipelines, model training workflows, or large datasets.
• Ability to translate research ideas into practical systems.

Responsibilities

• Build and maintain data pipelines that generate training datasets for ML models and experimentation.
• Contribute to infrastructure that supports distributed training workflows (e.g., PyTorch, Ray).
• Work with workflow orchestration tools (Airflow, Flyte, or similar) to support multi-stage ML pipelines.
• Improve reproducibility and reliability through dataset validation, monitoring, and testing.
• Partner with ML engineers to support experimentation and model iteration.
• Help optimize performance and efficiency across data processing and training systems.
• Contribute to the evolution of our offline ML platform architecture as it scales.

Skills

Python

ML systems

Distributed systems

Data processing

PyTorch

TensorFlow

Ray

Airflow

Education

Bachelor's degree in Computer Science, Machine Learning, Systems, or a related field

Tools

Airflow

Flyte

Spark

Job description

Unity Technologies seeks a Machine Learning Engineer to join the Offline Infrastructure team, focusing on large-scale data pipelines and distributed model training. You will help generate training datasets, support multi-stage ML workflows, and collaborate with researchers to translate ideas into scalable systems.

The role blends research and production, offering exposure to PyTorch, Spark, and orchestration tools. Strong Python skills and a passion for reliable ML infrastructure are required.