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
==============
As a Machine Learning Researcher, you will help design, train, and evaluate foundation models that learn from large-scale biological data (genomics, epigenomics, single-cell, proteomics, clinical signals).
Depending on your strengths, you might skew more towards:
Modelling & algorithms
- new architectures, training objectives, scaling strategies, multi-task / multi-modal learning.
Applied research
- framing high-impact questions with clinicians and biologists, building end-to-end disease models, and stress-testing them on real data.
Analysis & insight
- probing model internals, interpretability, mechanistic understanding, biomarker discovery.
Systems & efficiency
- if you enjoy it, helping push training, data, and inference infrastructure to the next scale.
The role is deliberately broad: we're looking for exceptional ML talent with strong research instincts, not a single CV template.
What you'll work on
-----------------------
You won't do all of these on day one; think of this as the space of things you may own.
Design and implement
ML models for large-scale biological data
, from pre-training to task-specific fine tuning.
Partner with biologists, clinicians, and data scientists to
translate biological and clinical questions into tractable ML problems
.
Run
end-to-end experiments
: dataset curation, training, evaluation, error analysis, and iteration.
Develop and refine
evaluation suites
for robustness, generalisation, and clinical relevance (e.g. across cohorts, sites, populations).
Explore
multi-modal and multi-task training
across genomic, epigenomic, transcriptomic, proteomic and clinical signals.
Perform
in-depth model analysis
to extract mechanistic or biomarker-level insights, not just metrics.
Collaborate on
papers, internal memos, and external communication
of key research results.
(Optional / plus) Contribute to
scaling and optimisation
of training and data pipelines, in close collaboration with research engineers.
Expected Growth
===================
This is illustrative; we know great people ramp differently.
1 month:
You've reproduced key baselines, run initial experiments on our internal datasets, and are comfortable with our training stack.
You've shipped your first improvements (e.g. better objective, data pre-processing, or evaluation variant) and presented results to the team.
3 months:
You own a
research thread
: a model family, disease application, or methodological idea.
You're independently designing experiments, refining hypotheses, and coordinating with relevant partners (ML, wet lab, clinical).
6 months:
You've delivered
meaningful research impact
: a stronger model, a new capability, a better biomarker, or evidence that changes our direction.
You are a go-to person for your area, helping others design experiments, debug models, and evaluate results.
Why Join Us:
================
Direct patient impact:
Your work sits on the critical path to earlier detection and better treatment of devastating brain diseases.
End-to-end environment:
We run the full stack from data generation to models to clinical studies, giving you an unusually tight feedback loop.
Exceptional peers:
You'll work with a small, high-calibre team across ML, biology, and clinical medicine.
High autonomy, high bar:
You'll have genuine ownership over problems that matter, with the expectation of operating at a very high standard.
Who You Are
===============
You likely recognise yourself in several of these:
Motivated by
advancing human health
through AI, especially in neuroscience and complex disease.
Deeply
curious
, with a habit of reading papers, prototyping ideas, and stress-testing your own assumptions.
Comfortable doing
real engineering work
in service of research - but see yourself first and foremost as a
researcher
.
Enjoy collaborating across
disciplines
and explaining your work to people with very different backgrounds.
Able to stay with
hard problems
for a long time, and to make progress even when the path isn't obvious.
Ideal experience
--------------------
We don't expect you to check every box. Strong applicants often have depth in some of these and interest in growing into others.
Strong background in
machine learning
or a closely-related field (e.g. deep learning, statistics, optimisation).
+ Industry, academic, or hybrid paths are all welcome. Demonstrated experience
and at least one major ML framework (PyTorch, JAX, or TensorFlow).
Experience designing and running
non-trivial experiments
: controlling for confounders, building robust baselines, and doing thorough error analysis.
Ability to
write clearly
- whether in code comments, research docs, or papers.
At least one of the following (more is a plus, not a requirement):
+ Experience with
large-scale data
(e.g. 100B+ tokens or equivalent) or distributed training.
+ Background in
computational biology, genomics, epigenomics, neuroscience, or related areas
.
+ Work on
foundation models
(language, vision, or multi-modal) and interest in applying that to biology.
+ Infra/optimisation experience (e.g. FSDP/ZeRO, quantisation, compilation, custom kernels) - especially valuable, but not mandatory.
If you're unsure whether you "count" as an engineer or a researcher:
please apply
. We care about what you can do and how you think, not your current job title.
Location
------------
Based in San Francisco, US or London, UK. We support visa applications.
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.
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