
Technical Lead, Machine Learning
BJAK
full-time
Posted on:
Location Type: Remote
Location: Singapore
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Job Level
About the role
- Own end-to-end ML system execution: data pipelines, training workflows, evaluation systems, inference architecture, and deployment.
- Fine-tune and adapt models using state-of-the-art methods such as LoRA, QLoRA, SFT, DPO, and distillation.
- Architect and operate scalable inference systems, balancing latency, cost, and reliability.
- Design and maintain data systems for high-quality synthetic and real-world training data.
- Implement evaluation pipelines covering performance, robustness, safety, and bias, in partnership with research leadership.
- Own production deployment, including GPU optimization, memory efficiency, latency reduction, and scaling policies.
- Collaborate closely with application engineering to integrate ML systems cleanly into backend, mobile, and desktop products.
- Make pragmatic trade-offs and ship improvements quickly, learning from real usage.
- Work under real production constraints: latency, cost, reliability, and safety
Requirements
- You have built or shipped real ML systems used by people, not just demos.
- You are comfortable working with large models and understanding their failure modes.
- You write strong, production-grade code and care about system correctness.
- You are self-directed, pragmatic, and take full ownership of outcomes.
- You communicate clearly and collaborate well in small, high-trust teams.
Benefits
- Flexible working arrangements
- Professional development opportunities
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
machine learningdata pipelinestraining workflowsevaluation systemsinference architecturemodel fine-tuningGPU optimizationmemory efficiencylatency reductionproduction-grade code
Soft Skills
self-directedpragmaticownershipclear communicationcollaborationteamworkadaptabilityproblem-solvingcritical thinkingtrust-building