Principal Data Scientist / Algorithm Engineer

PhysicsX

ABOUT US PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software. We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations — empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive. WHO WE'RE LOOKING FOR As a Principal Machine Learning Engineer in Delivery, you are an experienced problem solver and technical leader who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple industries, lead technical initiatives, and excel at working directly with customers (and often side-by-side with them on-site) to embed cutting-edge AI models into tools that are useful and used. You’ve shipped ML systems end-to-end and at scale: you design, build and test reliable, scalable ML data pipelines; you know how to explore and manipulate 3D point-cloud and mesh data to enable geometry-aware modelling; you select the right libraries, frameworks and tools and make pragmatic product decisions that set Delivery up for success. Working at the intersection of data science and software engineering, you translate R&D and project outputs into reusable libraries, tooling and products. With at least 5 years industry experience (post Masters or PhD) in a commercial, non-research environment, you're ready to not only execute but also lead and mentor others. You're truly excited about taking ownership of complex work streams and guiding teams to success, while continuously improving the systems and solutions you work on to ensure they are practical, impactful and meet the evolving needs of our customers. THIS ROLE  As a Principal MLE, you'll work closely with our Data Scientists, Simulation Engineers, and customers to understand and define the engineering and physics challenges we are solving. You will iterate with customers and use your influence to drive decisions around reliable deployment with measurable outcomes. You'll: * Own the deployment of ML models and engineering surrogates (e.g., deep learning on CAE/CFD/FEA data, time‑series forecasting, anomaly detection, optimization & control) to customer production environments. * Communicate results and trade‑offs to senior stakeholders; steer roadmaps and influence product direction with evidence. * Lead scoping and architecture design for data/ML systems; define success metrics, delivery plans and quality bars. * Excel at building robust and scalable ML systems, training and inference pipelines and APIs, running both on cloud and on-prem environments. The tech stack you will use for this includes: Python, PyTorch, Pandas, fastAPI, Scipy, Kubeflow, among others. * Mentor and develop engineers and data scientists; provide technical direction and clear, calm decision‑making under pressure. * Travel to customer sites in North America, Europe, Asia, Oceania, for an average of 3-4 weeks per quarter, where you'll collaborate closely with customers to build solutions on-site. * Own the scoping of new projects and work-streams with existing customers and taking part in bringing new customers to PhysicsX. As a senior member of the team, you’ll significantly influence our technical direction and will be involved in shaping future solutions and products, while developing your skills as a technical leader.   OUR DELIVERY TEAMS DRIVE INNOVATION TO TURN AI MODELS INTO PRACTICAL SOLUTIONS - READ OUR BLOG TO LEARN MORE ABOUT HOW YOU’LL CONTRIBUTE TO THIS EXCITING JOURNEY!    We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics.    We collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with UK employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.

PhysicsX

ABOUT US PhysicsX is a deep-tech company with roots in numerical physics and Formula One, dedicated to accelerating hardware innovation at the speed of software. We are building an AI-driven simulation software stack for engineering and manufacturing across advanced industries. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations — empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive. WHO WE’RE LOOKING FOR You are a problem solver and builder, passionate about creating practical solutions that help customers make better engineering decisions. You can grasp and apply advanced engineering concepts across multiple industries, and you excel at working directly with internal and external stakeholders, often on-site, to develop high-fidelity simulation models that feed into AI tools that are both useful and used. You bring deep expertise in fluid mechanics, heat transfer, and multiphase modelling within bioprocess and chemical engineering environments. You are highly proficient in at least one of Star-CCM+, OpenFOAM, or Fluent, and experienced modelling the complex flow behaviour that arises in industrial bioprocess systems. You are adept at automating these tools to create scalable optimisation workflows. Experience in parametric CAD modelling (NX or CATIA) and coding in Python (or the ability to pick up new programming languages quickly) is an advantage. With 5–7 years of industry experience (post-MEng, MSc, or PhD) in a commercial environment, you are ready to hit the ground running. You are confident setting up simulations independently, interpreting complex results with rigour, and making sound decisions grounded in solid engineering judgement. WHAT YOU'LL DO * Proficiency in CFD solvers across open-source OpenFOAM and commercial platforms as a plus (Star-CCM+, Fluent or equivalent), including custom solver and boundary condition development. * Develop multiphase flow models for gas-liquid, solid-liquid, VOF, Euler-Euler/Euler-Lagrange approaches) across a range of industrial and process engineering applications. * Model non-Newtonian and complex fluid rheology modelling, including high-viscosity, shear-thinning, or particle-laden flow regimes * Reactive and coupled-physics flow modelling — link CFD with reaction kinetics, heat transfer, or domain-specific process models (e.g. biokinetic, combustion, or electrochemical frameworks) * Own meshing generation and strategy for complex industrial geometries, including rotating machinery, internal flow passages, spargers, and free-surface interfaces * Build robust parametric CAD models (NX, CATIA, or equivalent) tightly coupled with simulation pipelines, enabling automated design optimisation and DoE studies * Multi-physics model development end-to-end: geometry clean-up, meshing, solver setup, post-processing, and experimental data integration for model validation * Scale-up/scale-down methodology — translate small-scale experimental data to full-scale CFD models and iterating model fidelity against physical measurements * HPC experience: job scheduling, MPI-based distributed computing, GPU acceleration, and performance tuning for large-mesh transient simulations on cloud (Flux) and on-premise resources * Surrogate modelling and ML-CFD coupling — build reduced-order or AI surrogate models from high-fidelity CFD data to support design space exploration and process optimisation * Data pipeline literacy — structuring and curate CFD output datasets for downstream AI/ML training, active learning, and Pareto optimisation workflows; applying data sampling techniques (LHS, quasi-random, adaptive) to efficiently cover design space * Experimental validation workflows — compare simulation predictions against physical test data, interpreting discrepancies, and systematically improving model fidelity * Customer-facing delivery — partner with clients to scope and address complex engineering challenges via CAE and AI solutions; communicating results clearly, recommending actionable next steps, and balancing accuracy with efficiency under commercial deadlines ENGINEERING AND WORKFLOW * 5–7 years post-graduate experience  * MEng, MSc, or PhD in mechanical, chemical, or process engineering * Python scripting and simulation automation * DoE, surrogate modelling, and design space exploration * Parametric CAD modelling (NX or CATIA advantageous) * Strong written and verbal communication with technical and non-technical audiences   WHAT WE OFFER Build what actually matters Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society. This is work with real-world impact - and something you can be proud to stand behind. Learn alongside exceptional people Work with a high-caliber, collaborative team of engineers, scientists, and operators who care deeply about doing great work, and about helping each other get better. We come from diverse backgrounds, but we share a commitment to operating at the highest level and addressing some of the most complex challenges out there. If you’re ambitious, thoughtful, and driven by impact, you’ll feel at home. Influence over hierarchy We operate with a flat structure: good ideas win - wherever they come from. Questioning assumptions and challenging the status quo isn’t just welcomed, it’s expected. Sustainable pace, long-term ambition Building meaningful technology is a marathon, not a sprint. We believe in balancing focused, ambitious work with a life beyond it. Our hybrid model blends time together in our Shoreditch office with work-from-home days, giving you the flexibility to work sustainably while staying connected in person.   We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity. We strongly encourage individuals from groups traditionally underrepresented in tech to apply. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics.    We collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with UK employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.

CoMind

At CoMind, we are developing a non-invasive neuromonitoring technology that will result in a new era of clinical brain monitoring. In joining us, you will be helping to create cutting-edge technologies that will improve how we diagnose and treat brain disorders, ultimately improving and saving the lives of patients across the world. THE ROLE: The Data Science team at CoMind develops the algorithms and machine learning systems that transform raw optical interference signals from CoMind One into continuous, clinically meaningful measurements of cerebral blood flow, intracranial pressure, and autoregulation. Working at the frontier of photonics, physiology, and applied ML, the team's work directly determines what CoMind One can measure, how accurately, and under what clinical conditions. As Principal Data Scientist, you will be the technical authority for CoMind's data science function, setting methodological direction for signal extraction and ML modelling, personally driving the most complex and highest-impact problems, and providing expert guidance across the team. This is a senior individual contributor role: you will not manage people directly, but your technical leadership will shape how the entire team approaches its most challenging problems. You will work closely with R&D, Clinical, and Software Engineering. At CoMind, all team members work at least 4 days per week from our new Kings Cross offices, plus a flexible work-from-home day. RESPONSIBILITIES: * Own the technical direction for signal processing and ML model development on CoMind One, defining approaches, architectures, and evaluation frameworks that set the standard for the team * Lead the development and validation of the most complex data science components, from novel algorithm design through to evidence generation for regulatory submissions * Act as the primary technical reviewer and expert resource across the data science team, setting the bar for methodological rigour, reproducibility, and scientific integrity * Drive the design and execution of data collection and labelling strategies with Clinical teams, including ground truth definition, dataset governance, and performance benchmarking * Contribute to CoMind's IP and publication strategy, authoring and reviewing technical papers, patent applications, and regulatory documents * Represent the data science function in cross-functional technical forums, architecture reviews, and external scientific and clinical engagements * Identify and introduce new methods, tools, and approaches that advance CoMind's signal extraction and ML capabilities * AI is fundamental to our culture. It's not just a tool, but a core part of how we work, collaborate, and innovate. We expect all team members to embrace AI in their daily work and continuously find new ways to use it effectively. SKILLS & EXPERIENCE: * 15+ years of experience in data science, ML, or applied research, with a strong track record of independent technical leadership on complex, ambiguous problems * Deep expertise in time-series signal processing and physiological or biomedical ML, including hands-on experience developing and validating models on noisy, real-world physiological data * Demonstrated ability to take algorithmic work from research through to production-quality, validated implementation * Experience in a regulated industry (medical devices, diagnostics, pharma, or similar), with familiarity with algorithm validation and documentation requirements for software as a medical device * Strong record of scientific output: publications, patents, or equivalent evidence of original technical contribution and domain authority Nice to Have * Background in neuroscience, neuromonitoring, neurophotonics, and/or cerebrovascular physiology * Experience with optical signal processing - e.g. LiDAR, pulse oximetry, NIRS, laser doppler flowmetry, or related technologies * Familiarity with FDA regulatory pathways for AI/ML-based medical devices BENEFITS: * Company equity plan so all employees share in the success of the company * Salary-sacrifice pension scheme * Private medical, dental and vision insurance (medical history disregarded) * Group life assurance at 4x annual income * Comprehensive mental health support, including unlimited access to 1:1 sessions with trained professionals * Unlimited holiday allowance (+ bank holidays) and one week of remote working per quarter * Lunch voucher (£10) every day for JustEat and free dinner on those days where you need to work later * Twice weekly deliveries of fresh fruit and an extensive selection of snacks and drinks * YuLife subscription, allowing you to turn your daily steps and meditation into discounts at a range of stores * Access to Udemy for upskilling and professional development.