HEY,
BOSTON

Senior Data Engineer - HealthTech$150,000 - $200,000  Fully RemoteFull time / Permanent A fast-growing healthcare technology start up is looking for a Senior Data Engineer to join their team. They are actively working with large healthcare organizations across the U.S, helping them get more value from their data through AI-powered clinical tools. This work has a direct impact on how care is delivered and the data teams sit at the centre of that. This is a hands-on role. You will be building and owning data pipelines that feed real AI systems used by clinicians every day. Why JoinSmall, collaborative teams where senior engineers have real ownershipClear progression to director. The company is growing and promotes from withinCompetitive base salary, equity, flexible hours, and strong benefitsWork that has a tangible impact on patient care across the U.S.The Role You will join a small team responsible for integrating data from large healthcare organisations into a modern cloud data platform. Day to day, you will be building pipelines, validating data quality, and making sure the right data reaches the right systems reliably and on time. You will also contribute to shared tools and frameworks that make future integrations faster, work that scales well beyond your individual projects. What We're Looking For4 years of experience building production data pipelinesStrong SQL skills across large, complex datasetsProficiency in Python for data transformationExperience with cloud-based data platforms and distributed processing toolsComfortable working with healthcare data formats and standards, or willing to learn quicklyExperience with Azure cloud servicesUseful but not essential:Background in healthcare data or EHR systemsExperience with modern lakehouse architecturesExposure to real-time data pipelines or message-based data feedsExperience in a SaaS or multi-tenant environmentTech Stack Azure Data Factory - Databricks - Python - SQL - PySpark - CI/CD tooling - Healthcare data standards What Success Looks LikePipelines delivered on time, well tested, and clearly documentedData quality issues caught early — before they reach productionReusable components that speed up future workStrong working relationships with partner technical teamsNoteworthy - This is a full-time / permanent role and cannot be considered for C2C, C2H, or any other temporary contracts.

Senior Data Engineer - HealthTech$150,000 - $200,000  Hybrid - Houston, TX Full time / Permanent A fast-growing healthcare technology start up is looking for a Senior Data Engineer to join their team. They are actively working with large healthcare organizations across the U.S, helping them get more value from their data through AI-powered clinical tools. This work has a direct impact on how care is delivered — and the data teams sit at the centre of that. This is a hands-on role. You will be building and owning data pipelines that feed real AI systems used by clinicians every day. Why JoinSmall, collaborative teams where senior engineers have real ownershipClear progression to director. The company is growing and promotes from withinCompetitive base salary, equity, flexible hours, and strong benefitsWork that has a tangible impact on patient care across the U.S.The Role You will join a small team responsible for integrating data from large healthcare organisations into a modern cloud data platform. Day to day, you will be building pipelines, validating data quality, and making sure the right data reaches the right systems reliably and on time. You will also contribute to shared tools and frameworks that make future integrations faster, work that scales well beyond your individual projects. What We're Looking For4 years of experience building production data pipelinesStrong SQL skills across large, complex datasetsProficiency in Python for data transformationExperience with cloud-based data platforms and distributed processing toolsComfortable working with healthcare data formats and standards, or willing to learn quicklyExperience with Azure cloud servicesUseful but not essential:Background in healthcare data or EHR systemsExperience with modern lakehouse architecturesExposure to real-time data pipelines or message-based data feedsExperience in a SaaS or multi-tenant environmentTech Stack Azure Data Factory - Databricks - Python - SQL - PySpark - CI/CD tooling - Healthcare data standards What Success Looks LikePipelines delivered on time, well tested, and clearly documentedData quality issues caught early — before they reach productionReusable components that speed up future workStrong working relationships with partner technical teamsNoteworthy - This is a full-time / permanent role and cannot be considered for C2C, C2H, or any other temporary contracts.

We are seeking an experimental physicist with strong hands-on experience in atomic, optical, or quantum systems to help build and operate advanced experimental platforms. You will work directly with precision hardware for qubit control, measurement, and system scaling, contributing to the development of next-generation quantum technologies.This is a lab-focused role for someone who enjoys designing experiments, troubleshooting complex setups, and collaborating across disciplines to turn ideas into working systems. Responsibilities Design, build, and characterize optical, vacuum, and/or cryogenic experimental systemsImplement protocols for qubit preparation, control, and readoutIntegrate lasers, RF/microwave systems, control electronics, and data acquisitionAnalyze experimental data and optimize performance and stabilityTroubleshoot hardware and control issues across the full experimental stackCollaborate with engineers and scientists to inform system design and scalingRequirements Ph.D. in Physics, Applied Physics, Electrical Engineering, or related fieldHands-on experience with experimental quantum systems (AMO, solid-state, or superconducting)Familiarity with qubit control, spectroscopy, or precision measurementStrong experimental problem-solving skillsExperience using Python or similar tools for experiment control and analysisA collaborative mindset and clear communication skills

Simulation Engineer Location: Onsite - Bay Area.Company: High-growth AI startup (stealth / early-stage)Focus: Physics-based simulation to ML-driven systemsOverviewOur client is building a new class of AI systems designed to understand and operate within real-world physical environments. The company sits at the intersection of simulation, machine learning, and industrial systems, with a focus on turning high-fidelity simulation data into scalable, production-grade intelligence.They are hiring Simulation Engineers across multiple domains who can bring deep subject-matter expertise and translate complex physical systems into computational models that can be learned, optimised, and deployed. This is not a pure research role. It is for engineers who have built and used simulation systems in real-world environments and understand how those systems behave under production constraints.Key Areas of HiringCandidates should come from one of the following domains:Bioreactors / Bioengineering (top priority)CFD / Fluid Dynamics (medical devices or industrial systems)Aerospace (flight physics, aerodynamics, control systems)Fixed-Wing Drones / UAVsAviation (commercial or defence aircraft systems)Space / Rocket SystemsWhat You’ll DoDevelop and apply high-fidelity simulation models across fluid, structural, thermal, biological, or aerodynamic systemsTranslate simulation outputs into ML-compatible datasets and representationsWork closely with ML and AI teams to enable surrogate modelling, optimisation, and system-level learningImprove simulation performance, scalability, and reliability across large-scale compute environmentsDesign end-to-end pipelines from simulation through to data generation, model training, and deploymentValidate and calibrate models against real-world data where availableWhat They’re Looking ForCore Requirements:Strong background in simulation engineering within a real-world domainExperience with tools such as OpenFOAM, ANSYS Fluent, STAR-CCM , Abaqus, ANSYS Mechanical, COMSOLExperience building or working with custom simulation frameworks (C , Python, MATLAB or similar)Solid understanding of physics-based modelling (fluids, thermodynamics, structural mechanics, control systems, or bio-systems)Experience working with large-scale simulations or HPC environmentsPreferred:Exposure to ML workflows (PyTorch, TensorFlow, surrogate models, optimisation loops)Experience generating or working with synthetic data from simulationsFamiliarity with distributed compute, GPU acceleration, or cloud-based simulation pipelinesBackground in companies such as:Medical Devices: Stryker, Medtronic, Boston Scientific, Zimmer BiometDrones/UAVs: Skydio, DJI, Autel, ParrotAerospace/Aviation: Boeing, Airbus, Joby, defence organisationsSpace: SpaceX, Relativity Space, NASA, Project Kuiper, Muon SpaceWhat Makes This DifferentYou are helping turn simulation into intelligence, not just running modelsDirect exposure to next-generation AI systems grounded in physicsOpportunity to work across multiple industries and problem domainsHigh ownership in shaping how simulation integrates into AI systems for the physical worldIdeal ProfileDomain expert first, not a generalistHas built simulations that informed real-world decisionsComfortable operating in ambiguous, early-stage environmentsInterested in bridging physics and machine learningHiring PriorityBioreactors / Bio-simulation (urgent)CFD / Fluid systemsAerospace / UAVAviationSpace systems