Full-stack ML Engineer, Valar Labs

Salary not provided

React

AWS

Docker

TypeScript

Node.js

PyTorch

Junior and Mid level

San Francisco Bay Area

Office located in Palo Alto, CA

AI-powered cancer diagnostics

Open for applications

AI-powered cancer diagnostics

21-100 employees

HealthcareB2BArtificial IntelligenceDeep TechSaaSMedTech

Open for applications

Salary not provided

React

AWS

Docker

TypeScript

Node.js

PyTorch

Junior and Mid level

San Francisco Bay Area

Office located in Palo Alto, CA

21-100 employees

HealthcareB2BArtificial IntelligenceDeep TechSaaSMedTech

Company mission

To remove the uncertainty from cancer treatment decisions, so physicians and patients don’t have to make educated guesses about therapy selection.

Job

Company

Role

Who you are

Bachelor’s or Master’s degree in Computer Science, Machine Learning or a related field, or equivalent practical experience
Hands-on experience training and evaluating deep learning models in PyTorch
Strong software engineering fundamentals and production experience, ideally with TypeScript, React, Node, Docker and AWS
Genuine interest in both halves of the role: research depth and shipping products to real users
Strong interest in deploying AI in healthcare, and in seeing it change how patients are treated
Daily fluency with agentic coding tools such as Claude Code and Codex
1-4 years of experience; exceptional new grads welcome
(Optional) Publications in medical AI or machine learning venues
(Optional) Experience with pathology, medical imaging or clinical data

What the job involves

Full-stack ML Engineers at Valar Labs work at the intersection of machine learning research and software engineering. They take a model from an experiment to a product that oncologists use every day, and they own the systems that keep it running
Run fine-tuning and post-training experiments on our pathology and clinical models, from hypothesis to result
Build the data loops that turn clinical and lab data into curated training and evaluation sets
Develop survival and outcome models alongside medical oncologists on clinically relevant questions
Deploy models into production and own their serving, monitoring and evaluation in a HIPAA environment
Ship full stack features across our clinician portal, revenue cycle product and lab operations tooling
Build agentic AI workflows that automate clinical and operational work, with the evals that make them trustworthy

Our take

About 1 in 5 people develop cancer in their lifetime, so finding better ways to treat it is a priority. Valar Labs is attempting to revolutionise cancer treatments with its AI-driven diagnostics.

The company specialises in analysing tumour microenvironments using computational histology AI (CHAI) tests to predict patient responses to therapies. This approach allows physicians to make informed, patient-specific decisions about cancer treatment, reducing uncertainty and improving outcomes.

The company has published numerous peer-reviewed studies that show its potential across multiple cancer types. Looking ahead, Valar Labs aims to expand its diagnostic capabilities, continuing to enhance precision oncology and improve patient outcomes globally. The significant funding it has raised will certainly help it on its way.

Steph

Company Specialist at Welcome to the Jungle

Company

Funding (2 rounds)

May 2024

$22m

SERIES A

Apr 2022

$4m

SEED

Total funding: $26m

Company benefits

Stock options - Every FTE becomes an employee and a shareholder
Health and Wellness - We offer generous coverage at no cost to FTEs, including medical, dental, and vision (we also offer dependent coverage at reasonable costs)
Retirement - FTEs are able to contribute into a traditional or a Roth 401(k) retirement savings account to build for the future
Flexible PTO - We offer a flexible time off policy so you can use it when you need it and recharge, without having to accrue hours

Company HQ

Evergreen Park, Palo Alto, CA

Leadership

Anirudh Joshi

(CEO & Co-founder)

Previously worked as a Deep Learning Researcher for PathAI and Curai. Prior to this, they worked as an Applied Scientist in Deep Learning for Microsoft.

Viswesh Krishna

(CTO & Co-founder)

Also founded Kanna, and is a Research Assistant at Stanford Artificial Intelligence Laboratory (SAIL).

Damir Vrabac

(COO & Co-founder)

Worked as a Machine Learning Intern for iZettle, and was a Researcher for Stanford University in Machine Learning.

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