Principal Scientist, Autonomous Cardiac Control Systems

LOCATION: San Diego, CA

HIRE TYPE: Full-time, Exempt

Job Summary 

Atrial fibrillation is chaotic, patient-specific, and constantly evolving. Drugs and ablation have advanced the field — but millions of patients remain inadequately served, and the underlying electrical disorder often goes uncontrolled. MaxWell Biomedical is on a mission to develop and deploy first-of-its-kind, non-destructive technologies that restore atrial synchrony, terminate atrial fibrillation, and improve hemodynamics in patients with cardiac rhythm disorders.

We don’t merely innovate at MaxWell, we advance. We carry responsibility with courage, not caution, because the status quo resists transformation because lives are on the line, and we are here for such a time as this. Join us as we create a fundamentally new therapeutic pathway for patients who remain inadequately served by existing AF treatments—and help shape the future of cardiac rhythm management.  

We are looking for a Principal Scientist, Autonomous Cardiac Control Systems to take intelligence further into real-world clinical use. The ideal candidate is a PhD-level researcher with strong RL and control systems foundations who was worked with physiological signals, time-series data, or safety-critical dynamical systems. You will use our in-house atrial electrophysiology simulator as a primary development environment to design, train, and evaluate reinforcement learning and control algorithms. In addition, you will work closely with experimental and clinical teams to translate these algorithms into real-world systems, supporting preclinical testing and ultimately clinical validation. 

This isn't a research position that ends in a paper. It isn't an engineering role executing a defined spec. It's both — and that's rare. You'll shape the algorithmic intelligence behind a therapy that doesn't yet exist in the market.

If you've been looking for a place where reinforcement learning meets real physiology — this is it.

What You’ll Do 

Reinforcement Learning System Development 

  • Architect and implement RL algorithms to personalize SRT pacing parameters. 

  • Utilize the existing in‑house AF electrophysiology simulation environment to train, test, and refine RL strategies. 

  • Develop safe‑exploration techniques and clinically appropriate reward functions. 

  • Integrate RL outputs with real‑time sensing and pacing capabilities. 

  • Develop model‑based RL, offline RL, or constrained RL approaches aligned with clinical safety needs. 

  • Additional responsibilities may be assigned by management as needed to support evolving business priorities. 

Using Existing Atrial Fibrillation Simulation Platform 

  • Work directly with the internal cardiac simulation environment to: 

  • Prototype RL agents 

  • Run large‑scale simulation experiments 

  • Perform stress tests and safety validation 

  • Generate synthetic datasets for algorithm training 

  • Collaborate with modeling experts to enhance or extend the simulator as needed for algorithm development. 

Control Systems & Algorithmic Safety 

  • Apply control theory to ensure pacing stability, reliability, and robustness. 

  • Use closed‑loop control principles to guide RL behavior in dynamical physiological systems. 

  • Perform safety analyses on RL policies before transitioning to benchtop or clinical contexts. 

Signal Processing & Machine Learning 

  • Develop ECG/EGM signal processing and feature extraction pipelines. 

  • Build classification and prediction models to identify AF patterns, conduction behavior, or therapy response. 

  • Support hybrid approaches combining ML predictions with RL control strategies. 

Experimental Design & Data Strategy 

  • Design benchtop or in‑silico experimental protocols that generate high‑value datasets for RL training and validation. 

  • Define data quality requirements, labeling strategies, and statistical validation frameworks. 

  • Work with clinicians and engineers to translate simulation‑derived strategies into practical patient‑specific tuning methods. 

Cross‑Functional Collaboration 

  • Collaborate with hardware, firmware, and signal‑processing engineers. 

  • Coordinate with regulatory and clinical teams to ensure algorithm safety and compliance. 

  • Communicate algorithm concepts, performance, and risks to executives and non‑technical stakeholders. 

  • Additional responsibilities may be assigned by management as needed to support evolving business priorities. 

What We’re Looking For 

  • MS or PhD in Electrical Engineering, Computer Science, Biomedical Engineering, or related field. 

  • Strong expertise in reinforcement learning and dynamical system control. 

  • Experience with RL libraries (PyTorch/TensorFlow + RL frameworks). 

  • Proficiency in Python and MATLAB for research and simulation. 

  • Strong background in signal processing and feature extraction. 

  • Experience with machine learning on time‑series/physiological signals. 

  • Understanding of algorithm validation, robustness, and safety requirements. 

  • Good teamwork and interpersonal skills. 

  • Ability to work well independently or within a cross-functional fast-paced team environment. 

  • Excellent organizational, computing and verbal/written communication skills. 

Preferred Qualifications 

  • Experience with medical device development, especially cardiac or electrophysiology systems. 

  • Familiarity with pacing concepts, arrhythmia mechanisms, or cardiac conduction modeling. 

  • Knowledge of regulatory guidelines for AI in medical devices. 

  • Experience with RL applied to physical systems, robotics, or other safety‑critical control tasks. 

  • Familiarity with evolutionary and population-based methods, e.g., Evolution Strategies, Genetic Algorithms, and Particle Swarm Optimization. 

  • Familiarity with Extremum seeking control algorithms. 

  • Familiarity with Black‑box evolutionary optimization (GA, PSO, CMA‑ES) with scheduled retuning. 

  • Familiarity with Bayesian optimization (BO) for controller parameters. 

  • Background in numerical modeling or electrophysiology simulation 

Physical Requirements 

The physical demands listed below must be met to perform the essential functions of this job successfully. Reasonable accommodation may be made to enable individuals with disabilities to perform the essential functions. 

  • Ability to work at a desk or computer workstation for extended periods of time 

  • Must be able to comply with company safety, quality, and regulatory procedures 

  • Occasionally required to lift/move up to 25 pounds 

  • Ability to travel domestically and internationally up to 10% of the time 

What We Offer 

MaxWell offers a total rewards package that reflects our stage, mission and commitment to investing in our people. 

  • Opportunity to share a transformative AF therapy device from inception 

  • Medical, Dental and Vision coverage, with MaxWell covering 60% of the cost for you and your dependents 

  • Market-competitive compensation, including an employee stock purchase plan 

  • Collaborative, fun, and mission-driven environment 

  • Monthly company-sponsored lunches 

How To Apply 

Please send your resume and a brief letter describing your interest in this role to talent@maxwellbiomed.com. Resumes and personal information submitted to MaxWell Biomedical are used solely for recruitment purposes and will be handled in accordance with applicable privacy law. We do not share your information with third parties without your consent. 

Recruitment Fraud Warning 

MaxWell Biomedical will never request payment, financial information, or gift cards at any stage of the recruitment process. All legitimate communication will come from @maxwellbiomed.com email addresses. We do not extend offers via text message or unofficial platforms. If you receive suspicious outreach claiming to be from us, do not engage and report it to scams@maxwellbiomed.com

Equal Opportunity Employer 

MaxWell Biomedical is an equal opportunity employer. We do not discriminate on the basis of race, color, religion, sex, national origin, age, disability, genetic information, veteran status, sexual orientation, gender identity, or any other protected characteristics. We welcome candidates from all backgrounds. 

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