Machine Learning Engineer, Offline Infrastructure (Entry-Level / New Grad)

Summary

Unity South APAC is a leading company known for its game engine technology. They are seeking a Machine Learning Engineer to join their Offline Infrastructure team, where the successful candidate will build and maintain data pipelines and contribute to scalable 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

• 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
• Experience with workflow orchestration systems (Airflow, Flyte, etc.)
• Exposure to large-scale data platforms (data lakes, warehouses, streaming systems)
• Publications or research in ML systems, distributed systems, or related areas

Qualifications

Must Haves

• 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

Nice to Haves

• Experience with workflow orchestration systems (Airflow, Flyte, etc.)
• Exposure to large-scale data platforms (data lakes, warehouses, streaming systems)
• Publications or research 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