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Machine Learning Engineer

Pay
$150,000–190,000/yearAnnual period assumed — pay source
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.
Read the full posting
Work setting
Hybrid — work setting source
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
Read the full posting
Employment
Not stated

What you’ll work on

Full posting
  • Design, build and test reliable, scalable ML data pipelines

  • Explore and manipulate 3D point cloud and mesh data

  • Own delivery of technical workstreams

  • Turn R&D results into reusable libraries, tooling and products

  • Work with customers on-site to build solutions

From the employer’s posting
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
translate the results of our R&D and projects into re-usable libraries, tooling and products
collaborate closely with customers to build solutions on-site
Education & alternatives
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.

Benefits in the posting

Full benefits wording
  • Learn alongside exceptional people
  • Influence over hierarchy
  • 💰 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.
  • 💳 Flexible Spending Account (FSA) – set aside pre-tax dollars for eligible healthcare expenses.

From the employer’s posting.

About PhysicsX

PhysicsX is the physics AI company for industrials.

In the employer’s words · Read in context

Apply at PhysicsX

Posting record

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Open 5 monthsWe first saw this posting 154 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.

Status in our records
Live
First seen by us
Jun 3, 2026154 days ago
Recorded sightings
69
Last seen by us
Nov 5, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Pay

In line with similar jobs

$150K–$190K against $166K–$240K, the middle half of what similar US postings state.

From 1,279 postings in the last year. Stated ranges, not salaries paid.

Time since we first saw it

Day 154

Up longer than most. Similar jobs usually come down between day 6 and day 69.

At PhysicsX, jobs usually come down by about day 143.

From 4,429 similar postings that came down, and 6 of PhysicsX’s. Coming down is not always a hire.

PhysicsX is hiring

8 open jobs

Open jobs by the week we first saw them, last 12 weeks.

  • Its jobs tend to stay up a long time
Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • Python
  • AWS
  • Azure
  • Docker
  • GCP
  • Kubernetes
  • MLflow
  • Spark
  • Dask
  • TensorFlow
Where the posting names them
- 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)
- Distributed computing frameworks (e.g., Spark, Dask) - Cloud platforms (e.g., AWS, Azure, GCP) and HP computing - Containerization and orchestration (Docker, Kubernetes)
- 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
- 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

Your next step

Complete your application on job-boards.eu.greenhouse.io. The employer’s form will show what is required.

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Has PhysicsX posted this job before?

Yes. We’ve followed 2 other Machine Learning Engineer jobs there since April 2026. One came down after 2 days. One is still up.

  1. New YorkStill up after 195 days, first seen Apr 24
  2. This jobUp 155 days so far, first seen Jun 3
  3. LondonCame down after 2 days, first seen Oct 14

About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

About us

Re-architecting Engineering for the Age of Intelligence

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

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 …

🚀 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.

📈 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. 
 
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. 
 
Source details

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Pay
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.
Location & working pattern

San Francisco, CA

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.
More source context
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

More relevant text appears in the full description.

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