Machine Learning Engineer
$150,000–$190,000 year
Remote · London, England, United Kingdom or New York City, New York, United States
Job Summary
Machine Learning Engineer in Delivery who collaborates with Data Scientists, Simulation Engineers, and customers to define and solve engineering/physics challenges. Responsibilities include designing, building and testing reliable ML data pipelines; exploring and manipulating 3D point cloud and mesh data; owning delivery of technical workstreams; creating analytics environments in cloud or on-prem; selecting libraries and tools; translating R&D results into reusable libraries, tooling, and products; applying engineering best practices and coaching peers. Travel to customer sites globally (3-4 weeks per quarter) to deploy solutions on-site. Strong emphasis on customer-facing, end-to-end ML deployments in industrial settings with a focus on impact and practical solutions.
Required Qualifications
- 2+ years industry experience in a data-driven role with exposure to software engineering concepts (versioning, testing, CI/CD, API design, MLOps)
- Experience applying ML methods to real-world engineering applications, including 3D graph/point cloud deep learning
- Background in Physics, Engineering, or equivalent
- Ability to ship ML systems end-to-end and to work with customers on-site
- Experience with Python and common ML libraries (e.g., TensorFlow, MLFlow)
- Experience with distributed computing frameworks (e.g., Spark, Dask)
- Experience with cloud platforms (AWS, Azure, GCP) and containerization/orchestration (Docker, Kubernetes)
- Strong problem-solving and communication skills
- Willingness to travel 3-4 weeks per quarter to customer sites
- Ability to translate R&D outputs into reusable libraries, tooling, and products
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