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Prima Mente · 3 weeks ago

Machine Learning Research Engineer

San Francisco

Full-time

Onsite

Mid, Senior Level

Prima Mente is a frontier biology AI lab focused on generating data and building biological foundation models. The Machine Learning Research Engineer will design, implement, and scale foundational AI models for multi-omics, driving breakthroughs in scientific understanding and contributing to transformative applications in medicine and biology.

Artificial Intelligence (AI)BiotechnologyNeuroscience

H1B Sponsored

Responsibilities

Implement high-performance ML algorithms optimised for massive-scale, ensuring reliability, efficiency, and scalability

Design, develop, and maintain robust experimentation pipelines enabling rapid iteration, precise evaluations, and reproducible research outcomes

Refactor and scale prototype research code into clean, maintainable, and performant repositories suitable for production-grade deployments

Create high-speed data processing workflows capable of efficiently handling large-scale datasets to accelerate experimentation and model development

Experimental design, prioritising high impact experiments with the highest signal:noise ratio

Qualification

Machine LearningDistributed ComputingData Pipeline DesignML FrameworksAlgorithm OptimizationLarge Scale ModelsHardware OptimizationCuriosityCommunication SkillsTeam CollaborationProblem Solving

Required

Deep understanding of state-of-the-art machine learning methodologies and proven experience in translating them into practical solutions

Solid foundation in distributed computing principles, parallel processing, and algorithmic efficiency

Experience optimizing ML algorithms for performance, memory efficiency, and compute resource utilization

Skilled in designing and implementing scalable data pipelines capable of rapid ingestion, transformation, and processing

Deep expertise in modern ML frameworks and tools (e.g., PyTorch, JAX, TensorFlow), and familiarity with state-of-the-art training and inference workflows

Skilled in clearly articulating complex ideas, effectively communicating why particular approaches succeed or fail, and providing insightful critical analyses

Experience of building highly collaborative research teams

Track record of working on hard problems for long periods of time

High agency with the ability to jump on any task as needed

Demonstrated experience training, optimizing, and deploying large-scale models (7B+ parameters)

Low level algorithm optimisation

quantization (8bit or lower)

JIT compilation

XLA/Mosaic/Triton/CUDA

Hardware optimisation (GPU/TPU/HPU)

Finetuning Optimization (QLora, QDora)

Large scale data above 2T tokens