Lead ML Engineer, Oncology Biomarker & Foundation Models

Artera Inc.; Northern (KY); Hybrid; USD 180,000 - 240,000; Full time

Benefits offered by this job

401k matching

Unlimited PTO

Equity

Job summary

Artera Inc. is seeking an experienced machine learning engineer to own AI biomarker development end to end — from clinical framing to regulatory submission and production deployment.

You will lead biomarker design using multimodal data (WSI, clinical, molecular) to predict outcomes and treatment benefit, advance foundation models, and ensure cross-site robustness and interpretability across scanners and sites.

Qualifications

• 5+ years of industry experience building deep learning systems in PyTorch (or TensorFlow).
• 2+ years of experience as a technical lead, launching and monitoring ML products in production.
• Demonstrated depth in oncology and biomarker development: familiarity with cancer biology and treatment pathways, clinical endpoints, risk stratification, and what makes a biomarker clinically actionable.
• Demonstrated project management ability — scoping, sequencing, and managing dependencies and risk across multiple teams on dated deliverables.
• Proven ability to communicate complex ML concepts effectively to cross-functional, non-ML collaborators.
• Experience mentoring or managing ML scientists and engineers.

Responsibilities

• Lead the technical effort and define the strategic vision for patient-facing products, in partnership with product, biostatistics, clinical development, and regulatory/quality.
• Design and build AI-based biomarkers on multimodal data — including whole-slide images, clinical variables, and molecular data — to predict patient outcomes, treatment benefit, and molecular traits.
• Advance our core self-supervised foundation models and the downstream architectures built on them (multiple-instance learning, time-to-event / hazard models, segmentation and classification components), with generalization as a first-order objective.
• Own score reproducibility across scanners, institutions, staining protocols, and patient populations.
• Develop and integrate mechanistic interpretability methods to explain model decisions, build clinician trust, and drive actionable model improvements.
• Architect tools and processes that streamline the end-to-end model development lifecycle — from prototyping through production deployment and monitoring — ensuring efficiency, reproducibility, regulatory compliance, and scale.
• Author and defend regulatory and quality documentation, and represent AI in design and development reviews.
• Plan and manage delivery: break multi-quarter programs into milestones, manage dependencies across AI, platform, biostatistics, and clinical teams, surface risk early, and hold submission and launch dates.
• Publish in peer-reviewed journals and present at clinical and ML venues; support external academic and industry collaborations.
• Mentor and coach machine-learning scientists and engineers, fostering their technical growth and collaboration skills, and raise the bar on scientific rigor, code quality, and written communication across the team.

Skills

Deep learning

Leadership

Communication

Mentoring

Tools

PyTorch

TensorFlow

Kubernetes

Flyte

AWS

Job description

Artera Inc. is seeking an experienced machine learning engineer to own AI biomarker development end to end — from clinical framing to regulatory submission and production deployment.

You will lead biomarker design using multimodal data (WSI, clinical, molecular) to predict outcomes and treatment benefit, advance foundation models, and ensure cross-site robustness and interpretability across scanners and sites.