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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer - **Company:** PhysicsX Inc. - **Location:** San Francisco, CA, United States - **Experience:** Experienced - **Salary:** $150,000.0 - $190,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Continuous Integration, Information Engineering, Distributed Computing Environment, Python (Programming Language), Machine Learning, Tensorflow, Simulation Software, Software Engineering, Computational Statistics, Test Data, Management of Software Versions, Google Cloud, Apache Spark, Deep Learning, Containerization, Kubernetes, Data Analytics, Dask, Machine Learning Operations, Api Design, Data Pipelines, Docker - **Published:** October 18, 2026 - **Apply:** https://www.careerbuilder.com/job-details/machine-learning-engineer-san-francisco-ca--f81363ea-7f9e-4838-841f-d0d737f3f0f2 ## About the Role As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple industries, 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. 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 2 years industry experience (post Masters or PhD) in a commercial, non-research environment. 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., * Experience applying Machine learning methods (including 3D graph/point cloud deep learning methods) to real-world engineering applications, with a focus on driving measurable impact in industry settings. * Experience in ML/Computational statistics/Modelling use-cases in industrial settings (for example supply chain optimisation or manufacturing processes) is encouraged. * A track record of scoping and delivering projects in a customer facing role * 2+ years' experience in a data-driven role, with exposure to software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps) * Building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., TensorFlow, MLFlow) * Distributed computing frameworks (e.g., Spark, Dask) * Cloud platforms (e.g., AWS, Azure, GCP) and HP computing * Containerization and orchestration (Docker, Kubernetes) * Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly * Excellent collaboration and communication skills - with teams and customers alike * A background in Physics, Engineering, or equivalent 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! ## Description About usRe-architecting Engineering for the Age of IntelligencePhysicsX is the physics AI company for industrials. The company's mission is to accelerate hardware innovation by overhauling what industrial engineering and manufacturing look like today. PhysicsX is building a new simulation software stack to deliver deep physics AI enablement across the entire engineering lifecycle. The company partners with leading organisations in aerospace & defence, automotive, semiconductors, materials, and energy & renewables, supporting them on some of their most critical and complex challenges. PhysicsX is headquartered in the United Kingdom, with offices in London, New York, and Singapore and an expanding presence in the Bay Area.Note: We are currently recruiting for multiple positions, however please only apply for the role that best aligns with your skillset and career goals.Who We're Looking ForAs a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple industries, 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. 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 2 years industry experience (post Masters or PhD) in a commercial, non-research environment. 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.We have hybrid offices in London, New York, and Singapore; this role is hybrid based in the San Francisco area.This Role As a Machine Learning Engineer, 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.What you will doWork closely with our simulation engineers, data scientists and customers to develop an understanding of the physics and engineering challenges we are solvingDesign, build and test data pipelines for machine learning that are reliable, scalable and easily deployableExplore and manipulate 3D point cloud & mesh dataOwn the delivery of technical workstreamsCreate analytics environments and resources in the cloud or on premise, spanning data engineering and scienceIdentify the best libraries, frameworks and tools for a given task, make product design decisions to set us up for successWork at the intersection of data science and software engineering to translate the results of our R&D and projects into re-usable libraries, tooling and productsContinuously apply and improve engineering best practices and standards and coach your colleagues in their adoptionYou'll also have the opportunity to 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.What you bring to the tableExperience applying Machine learning methods (including 3D graph/point cloud deep learning methods) to real-world engineering applications, with a focus on driving measurable impact in industry settings.Experience in ML/Computational statistics/Modelling use-cases in industrial settings (for example supply chain optimisation or manufacturing processes) is encouraged.A track record of scoping and delivering projects in a customer facing role2+ years' experience in a data-driven role, with exposure to software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps)Building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., TensorFlow, MLFlow)Distributed computing frameworks (e.g., Spark, Dask)Cloud platforms (e.g., AWS, Azure, GCP) and HP computingContainerization and orchestration (Docker, Kubernetes) Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend solutions quicklyExcellent collaboration and communication skills - with teams and customers alikeA background in Physics, Engineering, or equivalentOur 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!What we offerBuild what actually mattersHelp 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 peopleWork 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 hierarchyWe 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.And it doesn't stop there ... Equity options - share meaningfully in the company you're helping to build. 5% contribution to 401(k) - build long-term security with a strong retirement plan. Private health insurance - comprehensive cover for you, offering total peace of mind. Enhanced parental leave - 3 months full pay paternity and 6 months full pay maternity leave, to provide extra flexibility during the moments that matter most.️ 20 days of Annual Leave (+ Public Holidays) - because taking time to rest matters. Personal development - dedicated support for learning, development, and leveling up over time. Gympass / Wellhub (subsidized) - for you and up to 3 family members, supporting both physical and mental wellbeing. Flexible Spending Account (FSA) - set aside pre-tax dollars for eligible healthcare expenses.Watch this space, we're continuing to build this as we grow...Salary range:$150,000 - $190,000 depending on experience Seniority will be assessed throughout our interview process 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 employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.