Machine Learning Engineer
- Salary
- $150,000 - $190,000
- Level
- Mid
- Work type
- Hybrid · San Francisco
Not stated in the posting: visa.
Open. First seen 2 October 2026.
About the role
About us
Re-architecting Engineering for the Age of Intelligence
PhysicsX's standard text
PhysicsX is the physics AI company for industrials. The company’s mission is to accelerate hardware innovation by overhauling what industrial engineering and manufacturing look like today. PhysicsX is building a new simulation software stack to deliver deep physics AI enablement across the entire engineering lifecycle.
The company partners with leading organisations in aerospace & defence, automotive, semiconductors, materials, and energy & renewables, supporting them on some of their most critical and complex challenges. PhysicsX is headquartered in the United Kingdom, with offices in London, New York, and Singapore and an expanding presence in the Bay Area.
Note: We are currently recruiting for multiple positions, however please only apply for the role that best aligns with your skillset and career goals.
Who We're Looking For
As a Machine Learning Engineer in Delivery, you are a problem solver who stays anchored to impact. You are someone who can grasp advanced engineering concepts across multiple industries, and excel at working directly with customers (and often side-by-side with them on-site) to embed cutting-edge AI models into tools that are useful and used.
You’ve shipped ML systems end-to-end and at scale: you design, build and test reliable, scalable ML data pipelines; you know how to explore and manipulate 3D point-cloud and mesh data to enable geometry-aware modelling; you select the right libraries, frameworks and tools. Working at the intersection of data science and software engineering, you translate R&D and project outputs into reusable libraries, tooling and products.
With at least 2 years industry experience (post Masters or PhD) in a commercial, non-research environment. You're truly excited about taking ownership of complex work streams and guiding teams to success, while continuously improving the systems and solutions you work on to ensure they are practical, impactful and meet the evolving needs of our customers.
We have hybrid offices in London, New York, and Singapore; this role is hybrid based in the San Francisco area.
This Role
As a Machine Learning Engineer, you'll work closely with our Data Scientists, Simulation Engineers, and customers to understand and define the engineering and physics challenges we are solving. You will iterate with customers and use your influence to drive decisions around reliable deployment with measurable outcomes.
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
You'll also have the opportunity to travel to customer sites in North America, Europe, Asia, Oceania, for an average of 3-4 weeks per quarter, where you'll collaborate closely with customers to build solutions on-site.
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
- 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
Our delivery teams drive innovation to turn AI models into practical solutions - read our blog to learn more about how you’ll contribute to this exciting journey!
What we offer
PhysicsX's standard text
Build what actually matters
Help shape an AI-native engineering company at a formative stage, tackling problems that genuinely matter for industry and society. This is work with real-world impact - and something you can be proud to stand behind.
Learn alongside exceptional people
Work with a high-caliber, collaborative team of engineers, scientists, and operators who care deeply about doing great work, and about helping each other get better. We come from diverse backgrounds, but we share a commitment to operating at the highest level and addressing some of the most complex challenges out there. If you’re ambitious, thoughtful, and driven by impact, you’ll feel at home.
Influence over hierarchy
We operate with a flat structure: good ideas win - wherever they come from. Questioning assumptions and challenging the status quo isn’t just welcomed, it’s expected.
And it doesn’t stop there …
PhysicsX's standard text
🚀 Equity options - share meaningfully in the company you’re helping to build.
💰 5% contribution to 401(k) - build long-term security with a strong retirement plan.
🏥 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, to provide extra flexibility during the moments that matter most.
☀️ 20 days of Annual Leave (+ Public Holidays) - because taking time to rest matters.
PhysicsX's standard text
📈 Personal development – dedicated support for learning, development, and leveling up over time.
💪 Gympass / Wellhub (subsidized) – for you and up to 3 family members, supporting both physical and mental wellbeing.
💳 Flexible Spending Account (FSA) – set aside pre-tax dollars for eligible healthcare expenses.
🔎 Watch this space, we’re continuing to build this as we grow…
Salary range:
$150,000 - $190,000 depending on experience
Seniority will be assessed throughout our interview process
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. To help make a change, we sponsor bright women from disadvantaged backgrounds through their university degrees in science and mathematics.
PhysicsX's standard text
We collect diversity and inclusion data solely for the purpose of monitoring the effectiveness of our equal opportunities policies and ensuring compliance with employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.
What this role asks for
Particular to this role
Docker · GCP · MLOps · MLflow · Spark · TensorFlow
Rare in PhysicsX's other 31 open postings.
In most of PhysicsX's ads
Machine Learning · Python
Named in most of its open postings, whatever the role.
73% of this description is written for the role. The rest is PhysicsX's standard text, folded away below.
Read against PhysicsX's other open postings on this site.
The team: Delivery HIRES STEADILY
This role is one of 22 open in Delivery. 4 were posted in the last 30 days and the oldest in August: a team that hires all year rather than one being built.
WHAT THE TEAM WORKS WITH, ACROSS ITS POSTINGS
Python (21 of 22), Machine Learning (20 of 22), Deep Learning (14 of 22), CATIA (8 of 22), FastAPI (7 of 22), AWS (6 of 22), Azure (6 of 22)
OTHER ROLES ON THIS TEAM
- Senior CFD Engineer posted Oct 16
- Delivery Engineer posted Oct 7
- Senior CFD Engineer - Multiphase posted Oct 5
- Simulation Engineer: FEA & Multi body simulation posted Sep 29
- CFD Engineer posted Sep 8
- Senior Simulation Engineer - Electromagnetics Specialist posted Aug 13
- Forward Deployed Software Engineer posted Jul 20
- CFD Multiphase & DEM Engineer posted Jul 13
- Senior CFD Engineer - Plasma Specialist posted Jul 13
- Forward Deployed Software Engineer posted May 6
- Machine Learning Engineer posted Apr 23
- Senior Forward Deployed Software Engineer posted Apr 21
- CFD Multiphase & DEM Engineer posted Apr 20
- Senior Forward Deployed Software Engineer posted Jan 11
- Principal CFD Engineer posted Jan 11
- Principal Machine Learning Engineer posted Jan 11
- Principal Data Scientist / Algorithm Engineer posted Jan 11
- Senior Machine Learning Engineer posted Sep 19
- CFD Engineer posted Sep 12
- Senior Machine Learning Engineer posted Aug 12
- Data Scientist posted Aug 12
From the team and dates on PhysicsX's own job board.
Salary context
64 other open postings titled Machine Learning Engineer state a salary: median USD 150,000 to USD 211,700 a year.
See Machine Learning Engineer salaries in San Francisco →
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