Unity
Posted 123 days agoVerified live 1d ago
Intern, Infrastructure
Brief overview
Bellevue, WAIn-person
UndergradOr in progress
$48–$54/hrStated range
PythonMachine learning systemsDistributed systemsLarge-scale data processingPyTorchTensorFlowRaySparkProblem-solvingData pipelinesModel training workflowsWorkflow orchestration (Airflow, Flyte)Large datasetsData lakesWarehousesStreaming systems
About the company
Unityunity.com
Unity [NYSE: U] offers a suite of tools to create, market, and grow games and interactive experiences across all major platforms from mobile, PC, and console, to extended reality.
Job description
Summary
Unity is the world’s leading game engine, powering play for more than 3 billion consumers each month. As an Infrastructure Intern on the Offline Infrastructure team, you will work on large-scale systems and contribute to building and evolving the infrastructure for machine learning workflows.
Responsibilities
- Build and maintain data pipelines that generate training datasets for machine learning models and experimentation
- Contribute to infrastructure that supports distributed training workflows (e.g., PyTorch, Ray)
- Work with workflow orchestration tools (e.g., 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
- Currently pursuing a degree in Computer Science, Machine Learning, Systems, or a related field (Bachelor's or Master's)
- Foundation in machine learning systems, distributed systems, or large-scale data processing (through coursework, 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)
- Strong problem-solving skills and the ability to translate ideas into practical systems
- Interest in building scalable, reliable infrastructure for machine learning
- Exposure to data pipelines, model training workflows, or large datasets (academic or applied)
- Experience with workflow orchestration systems (Airflow, Flyte, etc.)
- Exposure to large-scale data platforms (data lakes, warehouses, streaming systems)
- Research or projects in ML systems, distributed systems, or related areas
Qualifications
Must Haves
- Currently pursuing a degree in Computer Science, Machine Learning, Systems, or a related field (Bachelor's or Master's)
- Foundation in machine learning systems, distributed systems, or large-scale data processing (through coursework, 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)
- Strong problem-solving skills and the ability to translate ideas into practical systems
- Interest in building scalable, reliable infrastructure for machine learning
Nice to Haves
- Exposure to data pipelines, model training workflows, or large datasets (academic or applied)
- Experience with workflow orchestration systems (Airflow, Flyte, etc.)
- Exposure to large-scale data platforms (data lakes, warehouses, streaming systems)
- Research or projects in ML systems, distributed systems, or related areas
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
