🛠 Tech Stack

💼 About This Role

You'll join Unity's Offline Infrastructure team to build and evolve large-scale ML infrastructure powering training data generation and distributed model training. You'll bridge research and production, translating advanced ideas into systems that operate at scale. This role offers the opportunity to work on systems powering 3 billion monthly consumers.

🎯 What You'll Do

• Build and maintain data pipelines for training datasets
• Contribute to distributed training infrastructure (PyTorch, Ray)
• Support multi-stage ML pipelines with workflow orchestration
• Improve reproducibility through dataset validation and monitoring

📋 Requirements

• PhD in Computer Science, ML, or related field
• Strong foundation in ML systems or distributed systems
• Experience with Python and data-intensive workloads
• Familiarity with PyTorch or TensorFlow

✨ Nice to Have

• Experience with Airflow or Flyte
• Exposure to large-scale data platforms (data lakes, streaming)
• Publications in ML systems or distributed systems

🎁 Benefits & Perks

• 🏖️ Generous vacation and personal days
• 🧠 Mental Health and Wellbeing programs
• 🏋️ Commute subsidy
• 👶 Support for new parents
• 📚 Training and development programs

📨 Hiring Process

Estimated timeline: 2-4 weeks · AI estimate

1. 1Recruiter Screen· 30 min
2. 2Technical Interview· 60 min
3. 3Hiring Manager Interview· 45 min

🚩 Heads Up

• Requires PhD but title says 'Entry-Level' - may overqualify
• No visa sponsorship or relocation support