About Us: Artera is an artificial intelligence company dedicated to transforming cancer care. We’ve developed foundation models that analyze clinical and pathology data, generating actionable insights that guide therapy selection and improve outcomes for cancer patients. By continuously improving these models, we aim to uncover the biological mechanisms driving cancer progression.
We’re looking for experienced machine learning engineers to lead initiatives from 0 to 1, spanning applied product development and core algorithmic research. As a part of the 3rd generation of our core foundation model, you’ll lead efforts to identify new approaches to model training that amplify clinically relevant biology while remaining robust across datasets, institutions, and patient populations. You will design, build, deploy, and continuously improve multimodal models—combining whole-slide images with clinical and molecular data—to predict molecular traits and patient outcomes.
Essential Responsibilities:
Lead the technical effort and define the strategic vision for patient-facing products in collaboration with partners from product, biostatistics, and clinical development.
Develop and launch the 3rd generation of our core foundation model, delivering increased generalization and robustness.
Design and build AI-based biomarkers on multimodal data (including whole-slide images) to predict molecular traits and patient outcomes; and evaluate emerging technologies to continuously enhance product capabilities.
Architect and implement tools and processes to streamline the end-to-end model development lifecycle—from prototyping to production—ensuring efficiency, robust performance, regulatory compliance, and scalability.
Develop and integrate mechanistic interpretability methods to explain model decisions, build customer trust, and drive actionable improvements.
Drive and contribute to publications in scientific journals and presentations at machine-learning conferences.
Mentor and coach a team of machine-learning scientists and engineers, fostering their technical growth and collaboration skills.
Experience Requirements:
5+ years of industry experience using PyTorch or TensorFlow.
2+ years of experience as a technical lead, launching and monitoring machine-learning products in production environments.
Proven ability to communicate complex ML concepts effectively to cross-functional, non-ML collaborators.
Desired:
Track record of research contributions, including peer-reviewed publications and conference presentations.
History of external academic or industry collaborations.
Experience with self-supervised representation learning (e.g., MoCo, DINOv2).
Work Authorization Requirement:
This is a remote role open to candidates who are currently authorized to work either in the United States or in Canada without the need for current or future employment-based visa sponsorship. Artera does not sponsor visas for this position.
Eligible candidates may include:
Individuals authorized to work in the United States on a permanent basis (e.g., U.S. citizens, U.S. permanent residents), or
Individuals authorized to work in Canada (e.g., Canadian citizens or Canadian permanent residents).
Visa Transfers (if needed)
Here are few posts from our teammates, partners and customer voices to highlight the work we do:
Artera Shapes the Future of Cancer Treatment Using Machine Learning on AWS
How Artera AI test allowed Bruno to avoid hormone therapy
Startups are using AI to predict responses to Cancer Drugs
ArteraAI validates its Prognostic Model in Advanced Prostate Cancer
How Artera Enhances Prostate Cancer Diagnostics Using AWS
Equal Employee Opportunity:At Artera, we value bringing together individuals from diverse backgrounds to develop new andinnovative solutions for patients and physicians. As an equal opportunity employer, we do notdiscriminate on the basis of race, color, religion, national origin, age, sex (including pregnancy),physical or mental disability, medical condition, genetic information gender identity orexpression, sexual orientation, marital status, protected veteran status, or any other legallyprotected characteristic.
