Machine Learning Engineer – AI Team (Global Digital)

Populous; Greater London; On-site; GBP 150,000 - 200,000; Full time

Job summary

A leading design firm in London seeks a Machine Learning Engineer to join their AI Technology Team. You will develop and integrate machine learning models, focusing on natural language processing and generative AI. This role offers the chance to impact the built environment through innovative AI solutions, while working within a supportive and diverse team environment.

Benefits

Hybrid working

Gym membership discounts

Opportunity to attend events at Populous-designed venues

Qualifications

• Several years of experience in machine learning engineering or applied ML roles.
• Strong Python programming skills and familiarity with ML libraries.
• Experience integrating machine learning models into workflows and applications.

Responsibilities

• Develop and fine-tune machine learning models, particularly in NLP and computer vision.
• Implement and maintain APIs for inference and batch jobs within production systems.
• Collaborate with developers to embed ML capabilities in user-facing applications.

Skills

Machine learning engineering

Python programming

ML libraries (e.g. scikit-learn, PyTorch, TensorFlow)

REST APIs operationalization

Data handling (structured and unstructured)

Tools

AWS

Azure

GCP

MLflow

Job description

We design the places where people love to be together — and we can’t do it without you.

Populous is all about people — it’s in our name. Attracting and retaining talented people who are passionate about their work is what makes us thrive. As a global firm, we have established roots in cities across the world, uncovering the very best local talent. The diversity of our team is our greatest strength and one of the most powerful sources of our creativity. We believe in supporting each other, coming together as a team to make sure everyone is fulfilled professionally, creatively, and personally.

Why Work With Us

Culture

Populous is built around the core values of integrity, entrepreneurial creativity, excellence and enjoyment. There are many milestones and celebrations along the way — yours and ours — and we share in these special moments together. We also reach beyond our offices to help make our local communities stronger, from engaging with university students and taking part in urban clean‑up projects to partnering with sports charities and promoting sustainable design.

Understanding people is what Populous is all about — and that begins with the people in our team. That’s why we have designed a comprehensive benefits program to support your employee experience at Populous and your life outside of work, including flexible work environments. From CrossFit in London, to the Noosa Triathlon in Australia to mental health check‑ins in the Americas, we have all kinds of initiatives to help you keep mind and body in top condition.

Diversity, Equity, Inclusion + Belonging

With more than 1,600 colleagues in 33 offices spanning four continents, we value the incredible range of talents, beliefs, experiences and perspectives of every person that makes up our team. You bring your authentic self and we’ll set the stage for you to succeed.

Professional Development

Populous is a team of people that are emotionally connected to their work. We wouldn’t have it any other way. From mentor programs and cross‑disciplinary design charettes to global conferences, you will have a wealth of opportunities to innovate and learn, shaping your career to meet your personal goals.

Our commitment to innovative design has earned us the top spot in architecture on Fast Company's list of the world's 50 most innovative companies.

"We are a team of fans, dreamers, thinkers and doers. We come together to amplify the magic of fandom and break barriers for the future of sports and entertainment."

What happens when you provoke designers to bring to life a digital footprint?

Tapping the Power of a Global Knowledge Network

Location: London, United Kingdom

Job Id:2730

# of Openings:1

About Populous

For more than 40 years Populous has had a singular focus – to draw people together around the things that they love, to be the leading design firm that specialises in places, spaces and events where people gather. Our success is defined by designing projects that are seen as the benchmark. We are committed to future innovation, anticipating and shaping the future of our industries.

Our team is made up of highly talented people with a range of skills, all integral to successfully bringing to life the places and experiences we design. As our company has grown, our expertise has expanded to encompass a wide variety of disciplines – including architecture, audiovisual consultancy, brand activation, design & build, events, food & beverage strategy, interior design, landscape architecture, urban design and wayfinding.

As we continue to bring to life award‑winning venues and experiences our EMEA Practice is looking for a Machine Learning Engineer – AI Team (Global Digital) based in our Putney studio.

About the Role

This role sits within our AI Technology Team. As a Machine Learning Engineer, you’ll help bring powerful AI capabilities to life—shaping tools that support staff across Populous. You’ll work across the full ML lifecycle, from data prep and model experimentation to deployment and ongoing optimisation.

You’ll collaborate closely with full stack developers and our AI Lead to prototype, fine‑tune and integrate machine learning models—particularly in natural language processing (NLP), generative AI and semantic search—into production systems that drive better outcomes in the built environment.

Key responsibilities include:

• Develop and fine‑tune machine learning models, particularly in NLP, computer vision and generative AI in collaboration with developers, data analysts and design team members.
• Adapt and integrate foundation models (e.g. Anthropic, OpenAI, Cohere) for targeted use cases.
• Implement and maintain APIs for inference, batch jobs and model access within production systems.
• Collaborate with developers to embed ML capabilities in user‑facing applications.
• Build end‑to‑end pipelines for data collection, pre‑processing, feature engineering and training.
• Work with structured, unstructured and spatial data across a variety of formats and sources.
• Manage model evaluations, experiment tracking and dataset versioning with reproducibility in mind.
• Monitor model performance and detect drift or degradation over time.
• Tooling & Infrastructure
  • Use ML frameworks such as PyTorch, TensorFlow and Hugging Face Transformers.
  • Operate within cloud platforms (AWS, Azure or GCP) for model training and deployment.
  • Leverage tools like MLflow, Weights & Biases or LangChain for model tracking and orchestration.
  • Contribute to the design and iteration of internal AI/ML‑powered design and productivity tools.
• Work in agile, cross‑functional teams alongside designers and domain experts.
• Stay current on research, tooling and trends in AI/ML - bringing new ideas into practice.
• Help shape our AI architecture and share your perspective in technical planning and team discussions.

Key requirements include:

We’re seeking an applied machine learning engineer who loves solving real‑world problems with data and AI. You’ll thrive here if you’re hands‑on, curious and excited to bring new capabilities into tools that shape spaces and human experience.

• Core Technical Skills
  • Several years of experience in machine learning engineering or applied ML roles.
  • Strong Python programming skills and familiarity with ML libraries (e.g. scikit‑learn, PyTorch, TensorFlow).
  • Experience integrating machine learning models into workflows and applications.
  • Solid understanding of vector search and embedding‑based systems (e.g. FAISS, Pinecone, Weaviate).
  • Comfortable operationalising models via REST APIs (e.g. FastAPI or Flask).
  • Proficient in handling both structured and unstructured data (text, images, spatial data).
  • Experience working in cloud‑based environments (AWS, Azure or GCP).
• Comfortable building and maintaining ML pipelines from prototype to production.
• Familiarity with tools for experiment tracking and version control (e.g. MLflow, Git or W&B).
• Strong communication skills—able to explain technical decisions to non‑technical collaborators.
• Effective working independently or as part of an interdisciplinary team.
• Mindset & Domain Interest
  • Research‑oriented and self‑motivated, with a desire to apply AI in tangible, impactful ways.
  • Interest in the built environment – whether through urban design, spatial data or large‑scale civic infrastructure.
  • Background in architecture, engineering, construction or location‑aware applications is a bonus, not a requirement.
• Preferred (but Not Required)
  • Experience with LLM orchestration frameworks (e.g. LangChain, Haystack).
  • Familiarity with retrieval‑augmented generation (RAG), prompt tuning or hybrid search architectures.
  • Exposure to MLOps workflows or orchestration tools (e.g. Airflow, Argo).
  • Understanding of AI governance topics such as data privacy, fairness and explainability.
  • Experience building internal tooling, design assistants or custom AI interfaces for non‑technical users.

About the Studio

Our Putney studio, which is also our EMEA Headquarters, is located on the banks of the River Thames, a short walk from Putney High Street and with excellent travel connections. Our employees enjoy a comprehensive and competitive benefits programme, as well as the opportunity to attend events at several Populous‑designed venues.

Why Join the Team?

• Work alongside passionate, creative individuals who lead their industry, transform ideas into reality and celebrate the beauty of human connection.
• Enjoy various benefits, such as hybrid working and gym membership discounts.
• Enjoy the opportunity to attend events at Populous‑designed venues.
• Connect and learn at regular social and knowledge sharing events including an annual conference and a weekend abroad Christmas party.

How to Apply

Populous is an equal opportunity employer. If you’re ready to utilise your skills to support our growing practice, click "Apply" to begin the application process. In your application, please include your CV and a one‑page letter of motivation (cover letter), salary expectations and availability.