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Founding Machine Learning Research Scientist

aspire life sciences search • United State
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AI Summary

Join an AI-native biotech as a founding member of its machine learning research team, designing next-generation foundation models for biological data. Key responsibilities include developing deep learning architectures, training scalable models on large biological datasets, and establishing research culture. Candidates must hold a PhD or equivalent in quantitative fields and demonstrate strong Python/PyTorch expertise with experience in distributed training.

Key Highlights
Founding member role shaping scientific vision and technical roadmap
Develop novel deep learning and foundation models for biology
PhD or equivalent in quantitative discipline required
Key Responsibilities
Design, develop and train next-generation deep learning and foundation models for biological data
Research novel model architectures, representation learning techniques and pre-training strategies
Build scalable machine learning pipelines capable of training across large and complex biological datasets
Design rigorous evaluation frameworks to benchmark, validate and continuously improve model performance
Collaborate closely with computational biologists and software engineers to translate research into robust production systems
Contribute to scientific publications, technical strategy and the long-term machine learning roadmap
Help establish best practices, technical standards and research culture as one of the founding members of the machine learning team
Stay at the forefront of machine learning research, identifying emerging techniques that can provide scientific and competitive advantage
Technical Skills Required
Python PyTorch Deep Learning Foundation Models
Benefits & Perks
Relocation Support
Relocation Allowance
Competitive six-figure salary
Meaningful equity
Comprehensive benefits
Nice to Have
Experience with genomics, transcriptomics, single-cell, proteomics or biological imaging data

Job Description


Location: San Francisco, California (Onsite)

Relocation Support & Allowance Available

Employment Type: Full-Time


Become a founding member of an AI-native biotech building the future of machine learning for biology.


This is an opportunity to join one of the most exciting early-stage AI companies in biotechnology as one of the founding members of its machine learning research team.


Backed by leading venture investors and fresh from a successful Seed financing, the company is developing next-generation foundation models to solve some of biology's most challenging problems. As one of the earliest technical hires, you'll work directly alongside the founders to shape the scientific vision, influence the technical roadmap and help build the research culture from the ground up.


This is not a role focused on applying existing models or maintaining production systems. It's an opportunity to invent new approaches, explore novel architectures and develop technology that could fundamentally improve the way new therapies are discovered and developed.


This is a fully onsite position based in San Francisco. The company believes breakthrough research happens through close collaboration, rapid experimentation and daily interaction between scientists and engineers. To support exceptional talent, relocation assistance and a relocation allowance are available for candidates moving to San Francisco from elsewhere in the US or internationally.


About the company


Our client is a venture-backed AI research company operating at the intersection of machine learning and computational biology.


Their mission is to develop large-scale biological foundation models capable of learning rich representations from complex molecular data, enabling deeper biological understanding and more accurate prediction of disease and therapeutic response.


By combining cutting-edge machine learning with large-scale biological datasets, they're creating technology designed to improve biomarker discovery, patient stratification and decision-making throughout the drug development process.


The team brings together researchers from leading AI organisations, technology companies and world-renowned academic institutions, creating an environment where scientific curiosity, technical excellence and ambitious thinking are genuinely encouraged. As an early-stage company, every team member has the opportunity to make a meaningful contribution to both the science and the future direction of the business.


The opportunity


As a Founding Machine Learning Research Scientist, you'll play a central role in defining both the research direction and technical foundations of the platform.


Working directly with the founders, you'll have the opportunity to explore new ideas, influence technical strategy and help establish the machine learning culture as the company scales.

This role is ideal for someone who enjoys solving difficult research problems, building novel machine learning models from first principles and seeing their work directly influence the future of an ambitious AI company.


Key responsibilities


  • Design, develop and train next-generation deep learning and foundation models for biological data.
  • Research novel model architectures, representation learning techniques and pre-training strategies.
  • Build scalable machine learning pipelines capable of training across large and complex biological datasets.
  • Design rigorous evaluation frameworks to benchmark, validate and continuously improve model performance.
  • Collaborate closely with computational biologists and software engineers to translate research into robust production systems.
  • Contribute to scientific publications, technical strategy and the long-term machine learning roadmap.
  • Help establish best practices, technical standards and research culture as one of the founding members of the machine learning team.
  • Stay at the forefront of machine learning research, identifying emerging techniques that can provide scientific and competitive advantage.


What we're looking for


We're seeking researchers who build machine learning models, rather than simply applying existing methods.


You'll likely bring many of the following:

  • PhD (or equivalent research experience) in Machine Learning, Computer Science, Computational Biology, Bioinformatics, Mathematics, Physics or another highly quantitative discipline.
  • Demonstrated experience designing, developing and training deep learning models from first principles.
  • Strong understanding of modern machine learning architectures, including Transformers, representation learning and foundation models.
  • Excellent Python and PyTorch programming skills.
  • Experience training models at scale using distributed computing and modern GPU infrastructure.
  • Experience working with large-scale biological datasets, including genomics, transcriptomics, single-cell, proteomics or biological imaging, is highly desirable. The specific biological modality is less important than the depth of your machine learning expertise.
  • Strong publication record or evidence of conducting impactful machine learning research.
  • Excellent communication and collaboration skills, with the ability to work effectively within a highly interdisciplinary research environment.
  • Curiosity, intellectual honesty and a passion for tackling genuinely difficult scientific problems.


Why join?


  • Become a founding member of the machine learning research team, helping shape the scientific direction, technical culture and long-term vision of the company.
  • Work directly alongside founders and exceptional researchers in a highly collaborative, research-driven environment.
  • Solve novel machine learning challenges with the opportunity to make a meaningful impact on the future of drug discovery.
  • Join at an early stage where your ideas, research and technical decisions will directly influence the evolution of the platform.
  • Competitive six-figure salary, meaningful equity, comprehensive benefits and relocation support for exceptional candidates.


Recruitment process


Our client is actively interviewing and is keen to engage exceptional candidates as they are identified rather than waiting for a formal application deadline.


The interview process is collaborative, technically rigorous and designed to provide candidates with a genuine understanding of the company's scientific vision, research challenges and long-term ambitions.


If you're excited by the opportunity to become a founding member of an ambitious AI-native biotech and help define the future of machine learning in biology, get in contact.



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