Lead ML Product Engineer

Radiant; Greater London; On-site; GBP 90,000 - 130,000; Full time

Benefits offered by this job

25 days annual leave

Cycle to Work Scheme

Gympass subscription

Private health insurance

Employee share scheme

Enhanced parental leave

Dedicated learning time

Open communication culture

Job summary

Radiant in London designs and operates AI-native infrastructure powering GPU workloads, multi-tenant control planes, and scalable AI systems for demanding environments. As an ML Product Engineer, you will turn Radiant's ML platform capabilities into usable, high-quality customer experiences across training, inference, APIs, SDKs, and developer tooling.

You will prototype and ship ML features, collaborate with product and engineering teams, and help define technical requirements and best

Qualifications

• Strong engineering background with ML infrastructure or developer tooling experience.
• Experience integrating ML frameworks and cloud services into product platforms.
• Excellent communication and cross-functional collaboration skills.

Responsibilities

• Build and prototype ML platform features, workflows, APIs, and tooling.
• Collaborate with Product to translate customer needs into technical solutions.
• Develop reference implementations across training, inference, and orchestration.
• Integrate ML frameworks with Radiant platform services (GPU, Kubernetes, storage).
• Engage with customers and internal teams to improve developer experience.

Skills

ML infrastructure

Developer tooling

Cloud platforms

AI products

Communication skills

Tools

Ray

Slurm

MLflow

Hugging Face

vLLM

Triton

LangChain

Job description

About our team:

Radiant is redefining how AI infrastructure is built.

We design and operate AI-native infrastructure platforms engineered for sovereignty, performance, and scale — powering GPU-native workloads, multi-tenant control planes, and high-performance AI systems for the most demanding environments. We are building purpose-built AI infrastructure from powered land, to compute, to software.

As we scale our operations and deploy capital into the next generation of AI infrastructure, we are looking to expand our finance team with leaders who can combine technical strength with execution excellence and are driven to build.

Radiant was established by Brookfield, a leading global alternative asset manager with over US$1 trillion of assets under management across real estate, infrastructure, renewable power and transition, private equity and credit. Brookfield’s global relationships, investment expertise and access to long-term institutional capital provide Radiant with a differentiated platform from which to develop, finance and operate AI infrastructure assets. This combination of entrepreneurial execution and institutional sponsorship enables Radiant to pursue large-scale GPU and AI infrastructure opportunities globally.

Job Summary:

As an ML Product Engineer, you will work at the intersection of product, machine learning, and cloud infrastructure, helping turn Radiant’s ML platform capabilities into usable, high-quality customer experiences.

You’ll work across GPU workloads, training, inference, APIs, SDKs, developer tooling, and platform integrations, partnering closely with product, engineering, infrastructure, and customers.

This is a hands-on technical role focused on rapidly prototyping, validating, and shipping ML platform capabilities that make it easier for customers to build and run AI workloads on Radiant’s platform.

Key Responsibilities:

• Build and prototype ML platform features, workflows, SDKs, APIs, and developer tooling.

• Work closely with Product to turn customer needs into working technical solutions and product experiences.

• Develop reference implementations across training, fine-tuning, inference, model serving, and orchestration.

• Integrate ML frameworks and tools with Radiant’s GPU, Kubernetes, storage, networking, and platform services.

• Work directly with customers and internal teams to identify friction and improve developer experience and time-to-value.

• Evaluate emerging ML infrastructure technologies and rapidly test their suitability for the platform.

• Support product discovery with technical prototypes, benchmarks, demos, and proof-of-concepts.

• Help define technical requirements, documentation, examples, and best practices for ML services.

Qualifications:

• Strong engineering experience, ideally in ML infrastructure, developer tooling, cloud platforms, or AI products.

• Strong understanding of:

• Familiarity with technologies such as Ray, Slurm, MLflow, Hugging Face, vLLM, Triton, LangChain, or similar.

• Comfortable moving quickly from an ambiguous customer problem to a working prototype or production implementation.

• Strong communication skills and comfortable working directly with product teams and customers.

What you bring:

• Builder mindset: You prefer proving ideas with working software.

• Product sense: You care about usability and customer outcomes, not just technical correctness.

• ML fluency: You understand how real ML workloads behave in production.

• Technical breadth: You can work across application code, ML frameworks, APIs, and infrastructure.

• Speed and ownership: You can take an idea from prototype through to something customers can actually use.

Our values:

• Set the standard: Every single day, you spot opportunities to constructively shake things up

• Inspire the change: There’s no blueprint for the future. You’ll embrace challenges and change

• You’re real and you’re true to yourself: We cherish and celebrate diversity so you’ll feel right at home whoever you are and whoever you’re talking to, you treat everyone the same.

Why should you join us?

What sets us apart is our blend of modern technology, competitive benefits, and an open, welcoming work culture that enables our people to thrive.

Here are just some of the great things you can expect from us:

• 25 days of annual leave

• A culture that emphasises results over hierarchy, process & ego: we place great emphasis on the quality, ingenuity and creativity of work.

• Open communication, regular feedback: we value smooth collaboration, direct and actionable feedback, and believe that leading with empathy and a growth mindset makes us better together.

• Learning Time: we all have dedicated learning time to focus on new skills, projects or interests that lay outside of your day-to-day job.

• Health & Wellbeing: we want everyone to feel healthy and happy, so we offer private medical insurance via Bupa.

• Cycle to Work Scheme: we’re committed to building a sustainable business, so we encourage cycling to work.

• Gympass subscription to a variety of gyms and wellbeing apps

• Participation in the company shares program

• Enhanced parental pay & leave