Principal Machine Learning Engineer

This is a fully remote position, open to applicants in Singapore.

📋 Description

• Develop and manage comprehensive ML pipelines that encompass data handling, model training, evaluation, inference, and deployment.

• Optimize and modify models utilizing cutting-edge techniques such as LoRA, QLoRA, SFT, DPO, and distillation.

• Design and implement scalable inference systems that effectively balance latency, cost, and reliability.

• Create and uphold data systems that ensure the availability of high-quality synthetic and real-world training data.

• Establish evaluation pipelines that assess performance, robustness, safety, and bias, collaborating closely with research leadership.

• Take charge of production deployment, focusing on GPU optimization, memory efficiency, latency reduction, and scaling strategies.

• Work in close partnership with application engineering to seamlessly integrate ML systems into backend, mobile, and desktop applications.

• Make practical trade-offs and swiftly implement enhancements, gaining insights from actual usage.

• Operate within real production constraints such as latency, cost, reliability, and safety.

⛳️ Requirements

• Solid foundation in deep learning and transformer-based models.

• Practical experience in training, fine-tuning, or deploying large-scale ML models in a production environment.

• Proficiency in at least one modern ML framework (e.g., PyTorch, JAX) with the ability to quickly learn others.

• Familiarity with distributed training and inference frameworks (e.g., DeepSpeed, FSDP, Megatron, ZeRO, Ray).

• Strong software engineering principles – you develop robust, maintainable, and production-ready systems.

• Experience in GPU optimization, focusing on memory efficiency, quantization, and mixed precision.

• Confidence in managing ambiguous, zero-to-one ML systems from start to finish.

• A proactive approach to shipping products, rapidly learning, and refining systems through iterative processes.

🏝️ Benefits

• Health insurance

• Flexible work arrangements

• Professional development opportunities