Machine Learning Research Engineer

About Prima Mente

Prima Mente's goal is to deeply understand the brain, to protect the brain from neurological disease and enhance the brain in health. We do this by generating our own data, building brain foundation models, and translating discovery to real clinical and research impact.

Role focus - Foundation Models for Biology

You will play a pivotal role in designing, implementing, and scaling foundational AI models and infrastructure for multi-omics at massive scale. Your work will directly drive breakthroughs in scientific understanding and contribute to transformative applications in medicine and biology.

• 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.

Expected Growth

• In 1 month you will be responsible for running initial experiments with state-of-the-art machine learning models, reviewing and implementing cutting-edge research papers, and optimizing existing code for efficiency and accuracy.
• In 3 months you will directly own and have created a prototype model architecture, demonstrated significant algorithmic improvements, and contributed to scaling methods for large-scale data ingestion and training.
• In 6 months, you'll have developed a high-performance version of a foundation model, implemented key algorithmic optimizations that boost scalability and throughput, and published internal benchmarks demonstrating significant research impact.

Why Join Us:

• Meaningful Impact: Contribute directly to research infrastructure that powers discoveries potentially impacting millions of lives.
• Innovation & Autonomy: Work at the forefront of AI and multi-omics, with the freedom to propose and implement state-of-the-art infrastructure solutions.
• Exceptional Team: Collaborate with talented colleagues from diverse backgrounds across ML, bioinformatics, and engineering.
• Growth Opportunities: Continuous learning and growth opportunities in a rapidly advancing technical field.

Culture Insight

What we are doing is extremely hard. Prima Mente is for great people. We are team players who appreciate challenges, want to be hands-on, and thrive on curiosity by throwing away assumptions. We are focused on excellence at pace and huge personal growth. We are strong communicators who are highly disciplined and rigorous.

Prima Mente operates with a flat organizational structure. We gain and share knowledge by contributing to multiple opportunities. Leadership is given to those who show initiative and consistently deliver excellence.

We arrange our lives so we can work in person as much as possible.

Our Values

• Exceptional performance at exceptional pace
  
  • The solutions we build demand uncompromising quality and rigour.
  • The problems we are solving are grave and present.
• Inquisitive discovery
  
  • We embrace curiosity and creativity.
  • Every question is a path to a transformational breakthrough.
• Radical candour
  
  • We practice unwavering honesty and transparency in all our challenges and interactions.
• Purposeful individuality
  
  • Every individual in our team is celebrated for their identity, uniqueness, and experiences.
  • We are invested in each one's bespoke personal development.
  • Nurturing individuality will supercharge our collective purpose and spirit.
• Patient impact at scale
  
  • We have a steadfast commitment to improve the health and well-being of patients globally.
  • Every experiment run, every dataset analysed, and every innovation developed, is a step towards achieving a scalable impact.

Who You Are

• Ambitious and Impact-Driven: You're inspired by working at the forefront of AI and biology, motivated by challenges that can significantly advance human health.
• Technical Excellence: You thrive in highly technical, complex environments and have a track record of turning cutting-edge research into robust production systems.
• Collaborative & Communicative: You excel at collaborating across disciplines, clearly articulating complex ideas, and driving alignment among research and engineering teams.

Ideal experience

• 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

Interview Process

Our intention is to run our interview process end to end within 2 weeks. You will interact with co-founders Ravi and Hannah, as well as every member of the technical team.