Machine Learning Research Engineer at Prima Mente - Frontier Biology AI Lab

You will design and scale biological foundation models to decode the human brain. Training 7B+ parameter models on trillions of tokens, you will bridge high-level research and production-grade systems. This role is central to developing AI that detects neurological diseases years earlier, directly translating frontier machine learning into life-changing clinical outcomes.

• Implement high-performance ML algorithms and distributed training infrastructure optimized for massive-scale multi-omic datasets.
• Design and develop robust experimentation pipelines to enable rapid iteration, precise evaluations, and reproducible research outcomes.
• Refactor research prototypes into clean, maintainable, and performant production-grade repositories suitable for large-scale deployments.

• Extensive experience training and deploying large-scale models (7B+ parameters) with deep expertise in PyTorch, JAX, or TensorFlow.
• Strong background in low-level optimization including quantization, CUDA/Triton, and hardware-specific tuning for GPU/TPU/HPU clusters.
• Proven track record of handling massive datasets (2T+ tokens) and building scalable data processing workflows for high-throughput training.

• Work at the absolute frontier of AI and biology, training 7B+ parameter models on 1.9T tokens of epigenomic data using a cluster of 256 H200 GPUs.
• Direct ownership of research direction and model architecture decisions in a flat organization where technical excellence profoundly shapes the company’s trajectory.
• Join a mission-critical lab solving the world's most complex biological system—the brain—to protect against Alzheimer's and other neurological diseases.