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About the Role

As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You will work directly with customers to embed cutting-edge AI models into useful tools, translating R&D and project outputs into reusable libraries, tooling, and products.

Responsibilities

• Work closely with simulation engineers, data scientists, and customers to understand and define engineering and physics challenges.
• Design, build, and test reliable, scalable, and easily deployable data pipelines for machine learning.
• 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 and make product design decisions.
• Translate R&D and project results into reusable libraries, tooling, and products.
• Continuously apply and improve engineering best practices and standards, and coach colleagues.
• Travel to customer sites in North America, Europe, Asia, Oceania (average 3-4 weeks per quarter) to collaborate and build solutions on-site.

Requirements

• At least 2 years of industry experience (post Masters or PhD) in a commercial, non-research environment.
• 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.
• Experience in ML/Computational statistics/Modelling use-cases in industrial settings is encouraged.
• A track record of scoping and delivering projects in a customer-facing role.
• 2+ years of experience in a data-driven role with exposure to software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps).
• Experience building machine learning models and pipelines in Python using common libraries and frameworks (e.g., TensorFlow, MLFlow).
• Experience with distributed computing frameworks (e.g., Spark, Dask).
• Experience with cloud platforms (e.g., AWS, Azure, GCP) and HP computing.
• Experience with containerization and orchestration (Docker, Kubernetes).
• Strong problem-solving skills and the ability to analyze issues, identify causes, and recommend solutions quickly.
• Excellent collaboration and communication skills with teams and customers.
• A background in Physics, Engineering, or equivalent.
• Must be a US citizen due to the nature of aerospace and defense work.

Skills

• Machine Learning
• 3D graph/point cloud deep learning
• ML/Computational statistics/Modelling
• Data Engineering
• Software Engineering
• Python
• TensorFlow
• MLFlow
• Spark
• Dask
• AWS
• Azure
• GCP
• Docker
• Kubernetes
• Problem-solving
• Collaboration
• Communication

Location

• New York (Office)
• Customer sites in North America, Europe, Asia, Oceania (Travel Required)

Work Type

• Hybrid
• On-site (Customer Sites)
• Full-time

Experience Level

• 2+ years industry experience (post Masters or PhD)
• Seniority assessed during interview process

Education Level

• Masters or PhD preferred

Salary/Compensations

• $150,000 - $190,000 depending on experience

Benefits

• Equity options
• 5% contribution to 401(k)
• Free team lunch 1x/week
• Private health insurance
• Enhanced parental leave (3 months full pay paternity, 6 months full pay maternity)
• 20 days of Annual Leave (+ Public Holidays)
• Personal development support
• Subsidized Gympass / Wellhub (for employee and up to 3 family members)
• Flexible Spending Account (FSA)

About the Company

• 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.
• Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive.

Equal Opportunity

• We value diversity and are committed to equal employment opportunity regardless of sex, race, religion, ethnicity, nationality, disability, age, sexual orientation or gender identity.
• We strongly encourage individuals from groups traditionally underrepresented in tech to apply.
• We sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics.
• We collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with UK employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.