Sam Warwick

Machine Learning Research ScientistLocation: Waltham, MA (Hybrid. Open to exceptional candidates outside Boston willing to spend approximately one week per month on site)Our client is an early-stage, venture-backed deep-tech company developing next-generation tools for subsurface characterization to accelerate clean energy deployment. Their work sits at the intersection of numerical physics, geoscience, and advanced machine learning, with a specific focus on reducing the cost and uncertainty of geothermal exploration.Founded by experts in physics and computation, the team is intentionally small, highly technical, and academically rigorous. They value first-principles thinking, intellectual curiosity, and a deep personal commitment to climate and clean energy impact. The company has over two years of runway following a recent pre-seed raise and is preparing for its next funding round.As a Machine Learning Research Scientist, you will help build research-grade machine learning models that tightly integrate physical laws with data. You will work closely with domain experts in physics simulation and software engineering to translate geophysical insight into principled ML architectures that can be trusted in real-world energy decisions.This is a selective, fundamentals-driven research role. Our client is not looking for a tooling-only ML profile, but for someone who thinks in mathematics and physics first.Key ResponsibilitiesDevelop machine learning models grounded in mathematical and physical principles to augment numerical physics simulationsDesign and implement algorithms that explicitly incorporate differential equations and physical constraintsCollaborate closely with physicists and engineers to translate geophysical understanding into ML architecturesInfluence the direction of core ML research within a lean, mission-driven teamBuild reproducible research workflows that feed directly into tools for clean energy deploymentRequired ExperienceMust-HavesPhD or equivalent research experience in Mathematics, Physics, or a closely related quantitative fieldStrong mathematical maturity with regular use of linear algebra, differential equations, and numerical methodsFirst-principles problem-solving approach rather than reliance on high-level ML abstractionsStrong Python skills and experience writing clean, research-grade ML codeGenuine motivation for climate, clean energy, and scientifically meaningful workNice-to-HavesExperience in scientific machine learning, including PINNs, operator learning, or surrogate modelingBackground in numerical simulation or high-performance computingExposure to geophysics, subsurface modeling, or energy-domain problemsWhat Success Looks LikeYou can clearly articulate the why, how, and what of your modeling decisions, particularly where physics and ML intersectYou produce reproducible research that improves the speed and quality of subsurface predictionsYou contribute to both foundational algorithms and practical tools used by scientists and engineersInterview ProcessVideo interview with the founding teamOn-site interview with the technical team over one full day

BMS & AI Edge Software Engineer Battery Systems | AI for Science | Energy Storage Our client is a publicly listed, AI driven energy technology company operating at the intersection of advanced materials science, battery engineering, and machine learning. Their mission is simple but ambitious: accelerate the global energy transition by using AI to fundamentally change how batteries are designed, validated, and operated. They are pioneers in applying AI directly to battery chemistry, materials discovery, and battery management systems, enabling next generation Li ion and Li metal batteries across transportation, energy storage, robotics, aviation, and defense adjacent applications. The Opportunity Our client’s Energy Storage Systems R&D group is seeking a BMS & AI Edge Software Engineer to design and deploy AI centric State of X (SoX) algorithms that run on edge devices. This role sits squarely between battery physics, embedded software, and applied machine learning. You will own algorithm development from concept through edge deployment, working closely with battery scientists, hardware engineers, and customer facing teams to bring production ready software into real world environments. Key Responsibilities Algorithm R&D for SoXDesign and implement SoX architectures covering charge, health, power, safety, degradation, and related metricsTranslate models and logic into production grade code running on edge devicesCollaborate with battery physicists and engineers on model selection and validationModel Design & OptimizationResearch and evaluate alternative algorithms to improve accuracy, robustness, and performanceOptimize models and software for real world operating constraintsPresent results internally and demonstrate measurable improvementsVerification & DeliveryTest and validate software as a production ready product using defined methodologiesSupport validation at customer sites or manufacturing plants as requiredEngage directly with customers to support deployment and technical approvalRequirements EducationPhD or Master’s in Electrical Engineering, Computer Science, AI, or a closely related fieldEquivalent hands on industry experience will be consideredExperience5 to 9 years of experience in Li ion batteries, BMS, or ESS software engineering (10 years for Senior level)Strong background in BMS sensing and control software including voltage, temperature, current, and diagnosticsSolid understanding of battery chemistries and characteristics such as OCV, C rate behavior, and impedanceExperience developing data driven or AI based algorithms for battery systems, ideally deployed on edge or cloudProven experience coding, integrating, validating, and delivering production softwareExposure to customer facing delivery or deployment projectsPreferred BackgroundBattery characterization methods such as GITT, dQ/dV, or similarPower electronics knowledge including DC/DC or DC/AC conversionFamiliarity with power delivery architectures such as UPS or battery backup systems for data centersWhat’s On OfferHighly competitive base salary and strong benefitsMeaningful equity participation in a publicly listed businessDirect impact on globally relevant energy and sustainability challengesWork alongside leading experts in AI, battery science, and engineeringLong term growth opportunities in a technically serious R&D environment