Machine Learning/Computer Vision Engineer, Gaming company

What You’ll Do

·       Design and build training pipelines, data workflows, and model integration systems

·       Develop infrastructure that accelerates research iteration and reduces turnaround time

·       Build systems for data collection, curation, and preprocessing at scale

·       Create tools and automation that move experiments toward production readiness

·       Optimize data pipelines for reliability, performance, and observability

·       Collaborate with ML researchers to understand their needs and remove technical blockers

·       Work on model serving infrastructure and integration with the production framework

·       Write clean, well-tested code that maintains high engineering standards

·       Participate in code reviews and help raise the engineering bar across the team

·       Contribute to shared tools, infrastructure, and cross-role projects (20% Time)

·       Work with the dual-leadership model (Engineering Manager and Tech Lead) to understand priorities and technical direction

·       Document systems and decisions to support team knowledge sharing

Must Have

·       Bachelor Degree or above in Computer Science

·       3+ years of professional software engineering experience in building production ML systems, training infrastructure, or research platforms

·       Proficiency in Python, additional experience with at least one other systems language (C++, C#, Java, Rust, or Go)

·       Hands-on experience with PyTorch or TensorFlow in production or research environments

·       Experience building or maintaining ML training pipelines or data workflows

·       Familiarity with model deployment, inference optimization, or MLOps practices

·       Excellent communication in English

Nice To Have

·       Experience with distributed training systems or GPU-accelerated computing

·       Knowledge of data versioning, experiment tracking, or ML metadata management

·       Familiarity with containerization (Docker) and orchestration tools

·       Contributions to open-source ML projects or research publications

·       Experience working in small, high-performance technical teams

·       Background in startups, high-growth environments, or consumer product companies

·       Passion for pushing technical boundaries and deep problem-solving