Machine Learning Engineer - AI Team (Global Digital)

About PopulousFor 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 and build, events, food and beverage strategy, interior design, landscape architecture, urban design and wayfinding.
This varied expertise enables us to transform neighbourhoods, revitalise cities, build relationships and create buildings, places and spaces that draw people together, from the Tottenham Hotspur Stadium to The Co-op Live Arena.
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 RoleThis 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 optimization.
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
Model Development and Integration
Develop and fine-tune machine learning models, particularly in NLP, computer vision, and generative AI in collaboration with developers and data analysts as well as with 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
Data Pipelines and Experimentation
Build end-to-end pipelines for data collection, preprocessing, 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 and 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 and Biases, or LangChain for model tracking and orchestration
Contribute to the design and iteration of internal AI/ML powered design and productivity tools
Collaboration and Innovation
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 requirementsWe''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 operationalizing models via REST APIs (e.g., using 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)
Development and Collaboration
Comfortable building and maintaining ML pipelines from prototype to production
Familiarity with tools for experiment tracking and version control (e.g., MLflow, Git, WandB)
Strong communication skills—able to explain technical decisions to non-technical collaborators
Effective working independently or as part of an interdisciplinary team
Mindset and 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 StudioOur 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 ApplyPopulous 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.
Want to learn more about us?
Find us here: Populous
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