Principal Machine Learning Engineer
Bjak · Remote · China ·
COMPENSATION
€•• – ••k
Listed on the employer's job board (Ashby)
- Principal level role
- Fully remote
- Python + PyTorch/JAX
- GPU-based systems
- High autonomy
Join a mission to create proactive, AI-native applications for email, tasks, and calendars that require minimal prompting. As a Principal Machine Learning Engineer, you will own the execution layer of the company's intelligence, bridging the gap between research capabilities and robust product features.
You will work across the entire model lifecycle, including data, training, evaluation, inference, and deployment. This hands-on leadership role requires operating at the intersection of research, systems engineering, and product development to ensure 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, robustness, and safety
- 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 translate models into products
- Make pragmatic technical trade-offs based on real-world performance
What you'll need
- Experience shipping production ML systems, not just research prototypes
- Strong understanding of large-model training, fine-tuning, and inference
- Solid software engineering and systems fundamentals
- Experience operating ML workloads at scale on GPU-based systems
- Ability to navigate ambiguous problems with strong technical judgment
- Bias toward experimentation, measurement, and shipping results
- High standards for correctness, reliability, and production quality
Stack
- Python
- PyTorch
- JAX
- GPU-based training and inference systems
How you'll work
- Small, high-talent-density team with broad ownership
- Engineers expected to exercise judgment and execute independently
- Fast decision-making balancing speed with engineering fundamentals
- Interviews conducted via virtual meetings or onsite
Hiring process
- Applications evaluated by technical team members
- Schedule 3 to 4 interviews maximum if fit is identified
- Prompt decision process valuing transparency and efficiency
- Offer extended upon demonstration of exceptional skills and mindset