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ArteraAI

Delivers CLIA-certified multi-modal prostate cancer test

Senior/Staff Machine Learning Scientist - Computational Pathology

Computer VisionConfirmed live in the last 24 hours
Full-timeRemote in USA$180k - $260k /yrRemote

About the Job

Requirements

  • At least 5 years of industry experience building deep learning systems, using PyTorch.
  • Hands-on experience with coding agents such as Cursor or Claude Code.
  • A track record of taking models beyond a notebook, including launching and monitoring machine learning products in production and evaluating them rigorously on messy, real-world data.
  • At least 2 years as a technical lead for complex machine learning programs, including scoping problems, setting technical direction, sequencing work, and managing dependencies and risk across teams on dated deliverables.
  • Demonstrated depth in oncology or biomarker development, including cancer biology and treatment pathways, clinical endpoints, risk stratification, and what makes a biomarker clinically actionable.
  • Ability to communicate complex machine learning concepts to cross-functional, non-machine-learning collaborators, including product, medical, and biostatistics teams.
  • Experience mentoring or managing machine learning scientists and engineers.

Responsibilities

  • Own an AI biomarker end to end, from problem framing with product, medical, and biostatistics partners through validation, regulatory submission, and production.
  • Lead the next generation of pan-cancer self-supervised pathology foundation models and downstream models, including multiple-instance learning, time-to-event models, and segmentation, with generalization as a first-order objective.
  • Own the reproducibility and robustness of model predictions across scanners, institutions, staining protocols, and patient populations.
  • Manage coding agents to propose and execute experiments, improve tooling efficiency, and identify biological insights that explain model behavior.
  • Serve as technical lead by setting technical strategy, breaking multi-quarter programs into milestones, managing dependencies across AI, platform, biostatistics, and clinical teams, surfacing risks early, and holding submission and launch dates.
  • Present findings to product, medical, and biostatistics teams; author and defend regulatory and quality documentation; and represent AI in design and development reviews to get models into patients’ hands.
  • Mentor machine learning scientists and engineers, and raise the bar on scientific rigor, code quality, and written communication across the team.
  • Publish in peer-reviewed journals, present at clinical and machine learning venues, and support external academic and industry collaborations.

Desired Qualifications

  • Machine learning experience with complex clinical data, including medical imaging, multi-omics, or longitudinal records.
  • Experience with weakly supervised learning such as multiple-instance learning, and survival analysis.
  • Experience with self-supervised representation learning such as DINOv3, and adapting medical foundation models to clinical tasks.
  • Machine learning experience in regulated environments, including FDA 510(k)/De Novo, Software as a Medical Device, design controls, or CLIA/LDT.
  • Experience with cloud-scale training and orchestration, such as Flyte/Union or AWS.
  • Prior regulatory experience.

About the Company

ArteraAI

Delivers CLIA-certified multi-modal prostate cancer test

ArteraAI develops personalized prostate cancer therapy solutions using multi-modal deep learning. Its flagship offering, the ArteraAI Prostate Test, is a high-complexity CLIA-certified clinical laboratory test performed in-house and used in clinical care. The test analyzes diverse data through advanced AI to tailor treatment decisions for individual patients. Unlike many competitors, ArteraAI integrates randomized phase III trial-informed science, in-house product development, and routine publications to support credibility, and targets a shift toward personalized, data-driven prostate cancer therapies. The company's goal is to equip healthcare providers with reliable, data-backed tools to personalize treatment plans, improving outcomes for patients while expanding adoption across hospitals, clinics, and other care settings.

Company size
51-200
Company stage
Debt Financing
Total funding
$181.6M
Headquarters
Los Altos, CA
Founded
2021

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