I’m working with a cutting-edge technology company that’s hiring a Software Engineer to join its ML Engineering team. You’ll build training pipelines, scalable data workflows, model integration systems, and tools that help researchers experiment faster and deploy models reliably.

This is a highly technical, hands-on role within a small team tackling complex challenges across ML systems, distributed computing, sensing technologies, and real-time inference.

1. Build scalable ML training pipelines and data workflows.
2. Develop infrastructure that accelerates research and experimentation.
3. Create systems for data collection, curation, and preprocessing.
4. Build model-serving and production integration capabilities.
5. Improve the performance, reliability, and observability of ML pipelines.
6. Work closely with researchers to remove technical bottlenecks.
7. Own systems from initial design through testing and production readiness.

1. At least three years of software engineering experience involving production ML systems, training infrastructure, or research platforms.
2. Strong Python development skills.
3. Experience with another language such as C++, C#, Java, Rust, or Go.
4. Hands-on experience with PyTorch or TensorFlow.
5. Experience building ML training pipelines or large-scale data workflows.
6. Familiarity with model deployment, inference optimisation, or MLOps.
7. Strong engineering fundamentals and a passion for solving technically difficult problems.

1. Distributed training or GPU computing experience.
2. Knowledge of experiment tracking, data versioning, or ML metadata platforms.
3. Experience with Docker and orchestration technologies.
4. Open-source ML contributions or research publications.
5. Experience within startups or small, high-performance engineering teams.

1. Build the technical foundations behind cutting-edge ML products.
2. Work at the intersection of machine learning research and production engineering.
3. Take clear ownership of technically challenging systems.
4. Collaborate closely with highly capable engineers and researchers.
5. Contribute to shared innovation projects beyond your core responsibilities.
6. Join a fast-moving environment where strong engineering directly shapes the product.

If you’re ready to accelerate your career and build ML infrastructure that pushes research into production, please apply with your latest resume and get in touch for a confidential conversation.

BAH Partners specialises in placing world-class technology and quantitative talent across Asia-Pacific’s leading financial institutions and technology-driven organisations.