Machine Learning Engineer

Unity Technologies SF offers a comprehensive benefits package and a collaborative, data-driven culture in Mountain View. This onsite role supports ML at scale on the Offline Infrastructure team, focusing on data pipelines for training data generation and distributed model training. The position carries a salary range of USD 104,100 to 152,000 per year and requires a bachelor’s degree.

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 snacks and refreshments
• Mental Health and Wellbeing programs and support
• Employee Resource Groups
• Global Employee Assistance Program
• Training and development programs
• Volunteering and donation matching program

Responsibilities

• Build and maintain data pipelines that generate training datasets for machine learning models and experimentation
• Contribute to infrastructure that supports distributed training workflows (for example PyTorch and Ray)
• Work with workflow orchestration tools (such as 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

Requirements

• Bachelor's degree in Computer Science, Machine Learning, Systems, or a related field
• Strong foundation in machine learning systems, distributed systems, or large-scale data processing (through research or projects)
• Experience with Python and working with data-intensive workloads
• Familiarity with ML frameworks (e.g., PyTorch, TensorFlow) and/or distributed systems (e.g., Ray, Spark)
• Experience (academic or applied) with data pipelines, model training workflows, or large datasets
• Strong problem-solving skills and ability to translate research ideas into practical systems
• Interest in building scalable, reliable infrastructure for machine learning

Technologies

• Python
• PyTorch
• TensorFlow
• Ray
• Spark
• Airflow
• Flyte

Additional information

• Relocation support is not available for this position
• Work visa/immigration sponsorship is not available for this position