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About the Role
As a Senior Machine Learning Engineer in Delivery, you will be an experienced problem solver and technical leader focused on impact. You will grasp advanced engineering concepts, lead technical initiatives, and work directly with customers to embed cutting-edge AI models into useful tools. You will translate R&D and project outputs into reusable libraries, tooling, and products.
Responsibilities
- Own the deployment of ML models and engineering surrogates to customer production environments.
- Communicate results and trade-offs to senior stakeholders, steering roadmaps and influencing product direction.
- Lead scoping and architecture design for data/ML systems, defining success metrics, delivery plans, and quality bars.
- Build robust and scalable ML systems, training and inference pipelines, and APIs for cloud and on-prem environments.
- Mentor and develop engineers and data scientists, providing technical direction and decision-making.
- Travel to customer sites in North America, Europe, Asia, Oceania for an average of 3-4 weeks per quarter to build solutions on-site.
- Own the scoping of new projects and work-streams with existing customers and participate in bringing new customers to PhysicsX.
- Influence technical direction and shape future solutions and products.
- Develop skills as a technical leader.
Requirements
- At least 3 years of industry experience (post Masters or PhD) in a commercial, non-research environment.
- Ability to grasp advanced engineering concepts across multiple industries.
- Experience shipping ML systems end-to-end and at scale.
- Experience designing, building, and testing reliable, scalable ML data pipelines.
- Knowledge of exploring and manipulating 3D point-cloud and mesh data for geometry-aware modeling.
- Pragmatic decision-making regarding product and technology choices.
- US citizens only due to the nature of aerospace and defense work.
Skills
- Python
- PyTorch
- Pandas
- fastAPI
- Scipy
- Kubeflow
- Machine Learning
- Data Science
- Software Engineering
- 3D point-cloud data manipulation
- Mesh data manipulation
- Geometry-aware modeling
- ML data pipelines
- ML systems
- Training pipelines
- Inference pipelines
- APIs
- Cloud environments
- On-prem environments
- Deep learning on CAE/CFD/FEA data
- Time-series forecasting
- Anomaly detection
- Optimization & control
Location
- North America
- Europe
- Asia
- Oceania
Work Type
- Hybrid
- On-site (customer travel)
Experience Level
- Senior
- 3+ years industry experience (post Masters or PhD)
Education Level
- Masters or PhD
Salary/Compensations
- $200,000 - $250,000 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
- Gympass / Wellhub (subsidized)
- 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.
- We operate with a flat structure where good ideas win.
- We believe in balancing focused, ambitious work with a life beyond it.
- We sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics.
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 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.