Machine Learning

Posted Yesterday
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San Francisco, CA
In-Office
Senior level
Artificial Intelligence • Information Technology • Software • Biotech
The Role
This role involves leading the development of AI systems to replace lab toxicity experiments, focusing on end-to-end ML architecture, research on chemistry-biology correlations, and building innovative models. Candidates should have strong ML skills, engineering abilities in Pytorch and Python, and a passion for both science and technology.
Summary Generated by Built In

Charter:

Be a founding member of a team setting out to build the first accurate AI systems for replacing lab and animal toxicity experiments with AI models

What are we looking for:

At the highest level, we only want to hire people who deeply inspire us and relentlessly push us to be better. They must level up the entire team, bringing significant energy and a sense of awe. High agency is critical: they see what’s important and they do it. Doing is the key but it should be guided by great taste for what truly matters. We’re looking for folks doing those niche hobbies and activities, the ones that might not make sense at first glance, but eventually reveal profound depth and passion when you dive in with them. These individuals act with intentionality or whimsical naivety like an immigrant in a new country, a performer trying to break out, or someone teaching themselves to code or garden. There must be a deep curiosity for all facets of Axiom, an ambition fueling their exploration of what we do. They want to do something here, to dive in headfirst, but they know they need to learn more, so they search with an insatiable hunger. They need to be cracked, technically excellent, obsessive masters of their craft. They're irrational; they could work in big tech, but they know it will not satisfy them. They want the pain of doing something brutally hard along with the riches and glory when it finally works.

What you will be doing:

  • Define the core end-to-end ML/AI system: wetlab data creation and data cleaning/processing; model architecture, training, and inference; compute infrastructure and model deployment

  • Lead the research & development of novel models for understanding the relationship between chemistry and biology

  • Architect and scale large models pretrained on paired chemistry and biological images

  • Applied research on optimizing, aggregating, and pooling embeddings

  • Become a research leader in novel and underserved areas: molecular graph representations, contrastive learning for chem/bio, semi-supervised learning on biological images, generative diffusion for biology

  • Grow as an entrepreneur as well as an engineer by building things from 0 to 1 while creating incredible value for scientists

  • Ship insanely great technology + products

We’re especially interested in:

  • Novel usage and application of embeddings in applied research settings

  • Deep learning research applied to non standard, thorny modeling problems

  • Multi-modal ML or unsupervised / self-supervised learning with multiple modalities

  • End to end applied deep learning research which makes it way into products

  • Ability to do the data dirty work in a way that translates to model improvements

  • Architects of ML systems from data generation, data processing, ML infra, training, and evaluation

What we look for:

  • Has done at least one piece of work, in industry or in academia, that shows exceptional machine learning talent

  • Strong engineering abilities (writing Pytorch NN code, working with data in numpy / pandas, interacting with training and inference pipelines, and writing more general software in Python and interacting with the cloud)

  • Extremely high potential to become a leader in the field of ML/AI research

  • Demonstrates extreme, obsessive curiosity for both the science and business

  • Matches our cultural phenotype:

    • high ownership and agency

    • cares deeply, curious

    • ambitious

    • practical, unpretentious, collaborative

    • focus on shipping awesome products to customers

Top Skills

AI
Machine Learning
Numpy
Pandas
Python
PyTorch
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The Company
HQ: San Francisco, CA
23 Employees
Year Founded: 2024

What We Do

Axiom helps scientists eliminate molecular toxicity by providing the most accurate and affordable predictive models. Our proprietary dataset includes more than 100,000 molecules tested in pooled primary human liver cells, tens of thousands of molecules with pharmacokinetic measurements, and thousands of molecules with curated clinical outcome data. Axiom's AI models offer higher accuracy than advanced in vitro systems like 3d spheroids, deep mechanistic understanding which untangles mitochondrial toxicity, ER stress, ROS formation, cytotoxicity, and more, and precise risk assessment for any molecule at relevant clinical dosage and clinical exposure levels. Our models remove the need for costly physical experiments, giving more accurate and cheaper toxicity assessments, and empowering scientists to make better-informed decisions and bring safer drugs to the clinic.

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