New York, United States of America Hybrid Employment

PhysicsX is hiring a Machine Learning Engineer

Responsibilities

  • Work closely with 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 libraries, frameworks and tools for a given task, make product design decisions to set us up for success
  • Work 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 products
  • Continuously apply and improve engineering best practices and standards and coach your colleagues in their adoption

Requirements

  • 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
  • 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
  • A track record of scoping and delivering projects in a customer facing role

Nice to Have

  • Experience in ML/Computational statistics/Modelling use-cases in industrial settings (for example supply chain optimisation or manufacturing processes)

Benefits

  • Equity options
  • 5% contribution to 401(k)
  • Free team lunch 1x/week
  • 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
  • 20 days of Annual Leave (+ Public Holidays)
  • Personal development – dedicated support for learning, development, and leveling up over time
  • Gympass / Wellhub (subsidized) – for you and up to 3 family members
  • Flexible Spending Account (FSA)
  • Hybrid work model blending time in New York office with work-from-home days

Work Arrangement

Hybrid — New York

Additional Information

  • Opportunity to travel to customer sites in North America, Europe, Asia, Oceania for an average of 3-4 weeks per quarter
  • Position is open to US citizens only due to aerospace and defense work
  • Help shape an AI-native engineering company at a formative stage
  • Work with a high-caliber, collaborative team of engineers, scientists, and operators
  • Flat structure: good ideas win - wherever they come from
  • Questioning assumptions and challenging the status quo is expected
  • Sustainable pace, long-term ambition: hybrid model supports work-life balance
About company
PhysicsX
A deep-tech company focusing on AI-driven simulation software for engineering and manufacturing across advanced industries, with roots in numerical physics and Formula One.
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Posted a month ago