Technical Lead, Machine Learning
Bjak · Remote · Singapore ·
COMPENSATION
€•• – ••k
Listed on the employer's job board (Ashby)
- Technical Lead, ML
- Fully remote
- Python + PyTorch
- Production-scale ML
- Small high-impact team
Lead the execution layer of intelligence for proactive, AI-native applications used by billions. You will transform model capabilities into reliable production systems, focusing on long-running workflows and minimal prompting.
This hands-on leadership role sits at the intersection of research, systems engineering, and product. You will own the full ML lifecycle, ensuring high reliability and real-world task completion.
What you'll do
- Own end-to-end ML systems from data and training to deployment
- Build and evolve training and fine-tuning pipelines for large models
- Design evaluation systems for capability, safety, and performance
- Architect high-performance inference systems optimizing latency and cost
- Create data pipelines for high-quality real-world and synthetic data
- Establish infrastructure for deploying, monitoring, and improving models
- Partner with research and engineering to integrate model capabilities
- Make pragmatic technical trade-offs based on real-world performance
What you'll need
- Experience shipping production ML systems, not just prototypes
- Strong understanding of large-model training, fine-tuning, and inference
- Solid software engineering and systems fundamentals
- Experience operating GPU-based ML workloads at scale
- Ability to navigate ambiguous problems with strong technical judgment
- Bias toward experimentation, measurement, and shipping results
- High standards for correctness, reliability, and production quality
Nice to have
- Comfortable working with large models and their failure modes
- Experience writing strong, production-grade code
Stack
- Python
- PyTorch
- JAX
- GPU-based systems
How you'll work
- Small, high-talent-density team
- Broad ownership and independent execution
- Fast decision-making with balanced engineering fundamentals
- Virtual meetings and/or onsite interviews
Hiring process
- Applications evaluated by technical team members
- Three to four interviews maximum
- Virtual meetings and/or onsite sessions
- Prompt decision after demonstrating skills and mindset