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

Summary

Unity South APAC is a leading company in the gaming industry, and they are seeking an Entry-Level Machine Learning Engineer to join their Offline Infrastructure team. The role involves building and maintaining data pipelines for machine learning models, contributing to distributed training workflows, and ensuring the reliability and efficiency of ML pipelines.

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