Founding Machine Learning Engineer | Evaluating Frontier Medical AI | $150k–$200k. Job in Santa Rosa Move Collective Jobs

About the Opportunity

This role is being recruited by CoffeeSpace on behalf of Tessel, an innovative startup focused on ML evaluation, clinical validation, and FDA regulatory strategies.

We are looking for a select group of outstanding ML researchers from our network. If you are a strong fit, we will connect you directly with the founding team.

Position: Founding ML Engineer

Compensation: $150k-$200k base + 1-3% equity

Start Date: ASAP

Employment Type: Full-time

About Tessel

Tessel is on a mission to revolutionize diagnostic AI, enabling earlier cancer detection and improved patient outcomes. But for this to happen, the AI must be reliable and effective.

Tessel builds the infrastructure needed to generate evidence that supports this reliability.

We collaborate with leading diagnostic AI companies and healthcare institutions to meticulously assess, explain, and continuously monitor AI model performance.

At Tessel, evaluation is not just a formality; it is vital to establishing trustworthy AI.

Supported by top-tier investors and part of StartX (Stanford's accelerator), we are well-positioned for success.

The Founding Team

Founded by Lucas Tao, who holds an MS in Computer Science from Stanford and has previous experience with the Stanford ML Group and AWS, our team brings extensive knowledge in ML systems, interpretability, and large-scale infrastructure.

The Opportunity

You will engage directly with medical imaging companies as they prepare for FDA 510(k) or De Novo submissions, managing these partnerships from start to finish—from framing evaluation queries to delivering actionable evidence that influences critical decisions.

This is not about building models; it’s about comprehending them: • Where do they excel? Where do they fail? • What compromises are made? What uncertainties exist?

Your output will provide rigorous, decision-grade evidence that is clear enough to guide internal choices, instill customer confidence, and endure regulatory scrutiny.

You will blend strong ML insights with customer judgment and consistently meet tight deadlines.

Required Qualifications • Demonstrated track record in machine learning or analytical work: notable projects, research publications, developed systems, or complex problem-solving. • Strong empirical ML instincts: adept at crafting experiments, analyzing failures, and debugging model behavior with statistical or representation-level analysis. • Experience in designing investigations, identifying misleading patterns, reasoning about distribution shifts and uncertainties, and differentiating signals from noise. • Comfortable handling messy real-world data, imperfect truths, and ambiguity. • High analytical proficiency in Python (from data to analysis to defensible conclusions). • Excellent communication skills to convey technical findings to both technical and non-technical audiences.

Preferred Qualifications • 3 to 5 years of experience or a significant research history, including published work related to model evaluation, development of medical imaging models, or similar expertise. • Experience in evaluating, validating, or troubleshooting real-world ML systems. • Familiarity with robustness, interpretability, or safety-critical evaluations. • Exposure to the fields of medical imaging, healthcare ML, or other safety-critical environments. • Experience collaborating with customers or cross-functional teams.

This Role Might Not Be For You If • You prefer optimizing metrics over investigating model performance on specific patient demographics. • You require clearly defined tasks and a stable scope to thrive. • You are uncomfortable sharing findings that involve some uncertainty. • You seek a purely technical role without any customer engagement.

Why Join Us?

This position offers a high-impact and ownership-driven opportunity. Your evidence will directly affect FDA submissions, hospital adoption rates, and ultimately patient outcomes.

Many startups are focused on model development. However, Tessel will set the standard in rigorous and ongoing evaluations within medical AI, influencing high-stakes AI governance across all sectors.

If you are motivated by accountability, ownership, and real-world impact rather than incremental improvements or industry hype, this role is for you.

Next Steps • Apply via the job post. • We will review applications and reach out for strong matches. • If aligned, we will connect you directly with the Tessel team.

If this position doesn't seem like a good fit, we may suggest and connect you to other exciting startup roles we're recruiting for, always with your consent.

A Note on Authenticity

This is a genuine, active role for which CoffeeSpace is recruiting on behalf of Tessel. We do not post speculative positions and engage directly with hiring teams.