Machine Learning Engineer
New York
PhysicsX
PhysicsX builds AI to accelerate innovation — improving the design, manufacturing and operation of complex products and machines.Note: We do not provide visa sponsorship in the US. Please only apply if you have the right to work in the US.
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 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
What you bring to the table
- 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
- 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
What we offer
- Be part of something larger: Make an impact and meaningfully shape an early-stage company. Work on some of the most exciting and important topics there are. Do something you can be proud of
- Work with a fun group of colleagues that support you, challenge you and help you grow. We come from many different backgrounds, but what we have in common is the desire to operate at the very top of our fields and solve truly challenging problems in science and engineering. If you are similarly capable, caring and driven, you'll find yourself at home here
- Experience a truly flat hierarchy. Voicing your ideas is not only welcome but encouraged, especially when they challenge the status quo
- Work sustainably, striking the right balance between work and personal life.
- Receive a competitive compensation and equity package, in addition to plenty of perks
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: APIs AWS Azure CI/CD Data pipelines Deep Learning Docker Engineering GCP Industrial Kubernetes Machine Learning Mathematics MLFlow ML models MLOps Physics Pipelines Python R Radar R&D Spark Statistics TensorFlow Testing
Perks/benefits: Career development Competitive pay Equity / stock options Flat hierarchy Startup environment
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