Machine Learning Engineer

PhysicsX; London; Hybrid; GBP 50,000 - 70,000; Full time

Job summary

A cutting-edge deep-tech firm in London is seeking a Machine Learning Engineer to design, build, and test scalable ML pipelines. The role involves direct collaboration with customers, exploring and manipulating 3D data, and integrating data science models with simulations. Candidates should have at least 1 year of industry experience and a relevant degree, with a strong focus on practical solutions.

Benefits

Equity options

10% employer pension contribution

Free office lunches

Flexible working

Hybrid setup

Enhanced parental leave

Private healthcare

Personal development

Work from anywhere

Qualifications

• At least 1 year industry experience in a commercial, non-research environment.
• Experience with ML tools and production environments.
• Ability to work directly with customers.

Responsibilities

• Design, build, and test reliable ML pipelines.
• Productionise ML models with validation and error analysis.
• Collaborate with simulation engineers.

Skills

ML pipeline building

3D point-cloud manipulation

Data science

Cloud-based analytics

Education

Masters or PhD in a relevant field

Tools

Python

TensorFlow

Scikit-learn

Job description

About us

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. By enabling high-fidelity, multi-physics simulation through AI inference across the entire engineering lifecycle, PhysicsX unlocks new levels of optimization and automation in design, manufacturing, and operations - empowering engineers to push the boundaries of possibility. Our customers include leading innovators in Aerospace & Defense, Materials, Energy, Semiconductors, and Automotive.

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 and builder who is passionate about creating practical solutions that enable customers to make better engineering decisions. You are someone who can grasp advanced engineering concepts across multiple industries, and you excel at working directly with customers (and often side-by-side with them on-site) to build, deploy and maintain production-grade ML tools that are useful, and used.

You design, build, and test reliable, scalable machine learning pipelines, and you know when to explore and manipulate 3D point-cloud and mesh data to enable geometry-aware modelling. You create analytics environments and resources in the cloud/on-prem that span data science, selecting the right libraries, frameworks and tools while making pragmatic product decisions that set delivery up for success. You thrive at the intersection of data sicence and software engineering, translating project outputs into tooling and products.

With at least 1 year industry experience (post Masters or PhD) in a commercial, non-research environment, you\'re ready to hit the ground running. You\'re truly excited about growing your technical expertise and are naturally inclined to take ownership of MLE pipelines, continuously improving the systems and solutions you work on to ensure they are practical, impactful and meet the evolving customer needs.

This Role

In this role, you\'ll work closely with our customers, as well as our team of Simulation Engineers, Data Scientists, and Software Engineers, to understand and define the engineering and physics challenges we are solving.

You\'ll build the foundations for successful, impactful solutions by:

• Designing, building and testing data/ML pipelines, that are reliable, scalable and easily deployable in production environment.
• Productionising ML models and surrogates with clear validation, error analysis
• Exploring and manipulating 3D point-cloud and mesh data, applying graph/geometry-aware techniques where appropriate
• Working closely with simulation engineers to ensure seamless integration of data science models with simulations.
• Engaging in open communication and presentation with both technical teams and customers, helping onboard users and co-develop with customers.
• There is a requirement to travel to customer sites in North America, Europe, Asia, Oceania, an average of 2-3 weeks per quarter, where you\'ll collaborate closely with customers to build solutions on site.

As the role evolves, there are exciting opportunities for growth as a technical lead, perfect for someone who is driven by taking ownership of more complex projects and leading the direction of future solutions.

What we offer

• Equity options - share in our success and growth.
• 10% employer pension contribution - invest in your future.
• Free office lunches - great food to fuel your workdays.
• Flexible working - balance your work and life in a way that works for you.
• Hybrid setup - enjoy our new Shoreditch office while keeping remote flexibility.
• Enhanced parental leave - support for life\'s biggest milestones.
• Private healthcare - comprehensive coverage
• Personal development - access learning and training to help you grow.
• Work from anywhere - extend your remote setup to enjoy the sun or reconnect with loved ones.

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 UK employment and equality legislation. This information is confidential, used only in aggregate form, and will not influence the outcome of your application.