United States onlyAbout Us: Artera is an AI startup that develops medical artificial intelligence tests to personalize therapy for cancer patients. Artera is on a mission to personalize medical decisions for patients and physicians on a global scale.
As a Senior Machine Learning Engineer at Artera, you will be a key technical leader driving the development of AI-based biomarkers that personalize cancer therapy. 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. Partnering with product, clinical development, and biostatistics, you’ll translate clinical needs into robust, well-validated solutions, incorporate mechanistic interpretability to explain decisions, and shepherd models from prototype to production in a regulated environment.
Essential Responsibilities:
- Lead the technical effort and define the strategic vision for developing novel biomarkers in collaboration with partners from product, clinical development, and biostatistics.
- 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).
Equal Employee Opportunity: At Artera, we value bringing together individuals from diverse backgrounds to develop new and innovative solutions for patients and physicians. As an equal opportunity employer, we do not discriminate on the basis of race, color, religion, national origin, age, sex (including pregnancy), physical or mental disability, medical condition, genetic information gender identity or expression, sexual orientation, marital status, protected veteran status, or any other legally protected characteristic.
