Staff Machine Learning Engineer
Bjak · Remote · United States ·
COMPENSATION
€•• – ••k
Listed on the employer's job board (Ashby)
- Staff level role
- Fully remote
- Python + PyTorch
- GPU systems focus
- High autonomy
Join a small, high-talent-density team dedicated to creating AI-native tools that organize daily life without complex prompting. As a Staff Machine Learning Engineer, you will own the execution layer of intelligence, ensuring models translate into scalable, reliable products.
You will work at the intersection of research, systems, and product, handling everything from data pipelines to inference optimization. The goal is to reduce hallucinations and deliver high-reliability workflows for billions of users.
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 real-world and synthetic training data
- Establish infrastructure for deploying and monitoring models
- Partner with research and engineering to improve product capabilities
What you'll need
- Experience shipping production ML systems, not just prototypes
- Strong understanding of large-model training and inference
- Solid software engineering and systems fundamentals
- Experience operating GPU-based ML workloads at scale
- Ability to navigate ambiguous problems independently
- Bias toward experimentation, measurement, and shipping
- High standards for correctness 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, hands-on team with broad ownership
- Fast decision-making and independent execution
- Interviews via virtual meetings or onsite
Hiring process
- Technical team evaluates applications
- Three to four interviews maximum
- Prompt decision after final interview