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NEXTMOVEFDE careers · United States

Machine Learning Engineer

Technologies

Python · TensorFlow · MLFlow · Spark · Dask · AWS · Azure · GCP · Docker · Kubernetes · 3D point cloud · mesh data

About PhysicsX

AI-native simulation software stack that replaces slow numerical physics with deep-learning surrogates for design, manufacturing, and operations in aerospace, automotive, semiconductors, energy, and materials.

Series B · 100–200 people

Job description

The full responsibilities and requirements are on the employer’s site.

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Source and classification

Production engineering · Evidence for this classification:

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. 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 For As a Machine Learning Engineer in Delivery, you
More from the job description

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. 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 For 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-awa [... source excerpt omitted ...] 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. Note: This position may require access to information protected under U.S. export control laws and regulations, including the Export Administration Regulations (EAR) and the International Traffic in Arms Regulations (ITAR). Please note that any offer for employment may be conditioned on authorization to receive software or technology controlled under these U.S. export control laws and regulations without sponsorship for an export license. This Role As a Machine Learning Engineer, you'll wo [... source excerpt omitted ...] neering 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 do Work closely with our simulation engineers, data scientists and customers to develop an understanding of the physics and engineering challenges we are solving Design, build and test data pipelines for machine learning that are reliable, scalable and easily deployable Explore and manipulate 3D point cloud & mesh data Own the delivery of technical workstreams Create analytics environments and resources in the cloud or on premise, spanning data engineering and science Identify the best li

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