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PhysicsX

Physics AI platform for industrial engineering

Senior Machine Learning Engineer

Applied Machine LearningUpdated on Nov 14
Full-timeNew York, NY, USA

About the Job

Requirements

  • At least 3 years of industry experience after a Master's or PhD in a commercial, non-research environment.
  • Experience shipping machine-learning systems end-to-end and at scale.
  • Ability to design, build, and test reliable, scalable machine-learning data pipelines.
  • Ability to explore and manipulate 3D point-cloud and mesh data for geometry-aware modelling.
  • Ability to select appropriate libraries, frameworks, and tools and make pragmatic product decisions.
  • Experience building robust, scalable machine-learning systems, training and inference pipelines, and APIs across cloud and on-premises environments.
  • Proficiency with Python, PyTorch, Pandas, FastAPI, SciPy, and Kubeflow.
  • Ability to understand advanced engineering concepts across multiple industries and work directly with customers, including on-site.
  • Ability to communicate results and trade-offs to senior stakeholders and influence decisions using evidence.

Responsibilities

  • Deploy machine-learning models and engineering surrogates, including deep learning on CAE/CFD/FEA data, time-series forecasting, anomaly detection, optimization, and 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 and machine-learning systems; define success metrics, delivery plans, and quality bars.
  • Build robust, scalable machine-learning systems, training and inference pipelines, and APIs, and run them in cloud and on-premises environments.
  • Mentor and develop engineers and data scientists, provide technical direction, and make clear decisions under pressure.
  • Travel to customer sites in North America, Europe, Asia, and Oceania for an average of 3–4 weeks per quarter to collaborate on-site and build solutions.
  • Scope new projects and work streams with existing customers and participate in bringing new customers to PhysicsX.
  • Work closely with data scientists, simulation engineers, and customers to define engineering and physics challenges; iterate with customers and drive decisions around reliable deployment with measurable outcomes.
  • Influence technical direction and help shape future solutions and products.

About the Company

PhysicsX

Physics AI platform for industrial engineering

PhysicsX uses physics-based artificial intelligence for industrial engineering, combining machine learning with physics simulations to shorten design and operation cycles for aerospace, energy, and automotive sectors. Its platform replaces multi-day simulations with near-real-time models that predict performance, helping teams test ideas faster while reducing emissions and costs. It differs from competitors by delivering physics-driven AI with fast, scalable simulations tailored to large, complex industrial systems, supported by a slate of major investors and industrial partners. The company aims to speed up product development and drive broad adoption of physics AI across industrial sectors.

Company size
201-500
Company stage
Series C
Total funding
$487M
Headquarters
London, United Kingdom
Founded
2019

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