Location
London

Hours
Contract role - hours to be agreed

Salary
Negotiable

About the Role
At AND Digital, we help organisations navigate the future of technology by combining human expertise, emerging tech, and AI to deliver better outcomes, faster. Since 2014, we have partnered closely with clients to solve complex challenges, build high-performing teams, and create lasting capability. As a Machine Learning Engineer, you will play a key role in deploying and operating AI and machine learning architectures within production ecosystems. You will work collaboratively in multidisciplinary teams, navigating ambiguity and solving complex problems to deliver high-quality, pragmatic, and outcome-focused solutions. This role requires clear communication and trust-building with clients and teammates, alongside a passion for continuous learning and adapting to new technologies.

Experience
- Hands-on experience deploying and operating AI and machine learning architectures in production environments
- Proficient in building high-volume batch processing systems, real-time microservices, automated continuous retraining, and system observability
- Deep understanding of the entire machine learning lifecycle, architecting sustainable solutions without compromising product outcomes
- Strong technical foundations in Python and SQL, with experience in modeling toolkits such as PyTorch, TensorFlow, and Scikit-learn
- Practical expertise with public cloud platforms, preferably Google Cloud Platform technologies including BigQuery, Vertex AI, and Dataflow
- Skilled in deployment pipelines, version control, and containerization platforms like Docker and Kubernetes
- Familiarity with advanced generative AI, Large Language Models, and agent orchestration tools such as ADK, LangChain, or AutoGen

About you
- You care deeply about producing high-quality work that delivers real value
- Comfortable navigating ambiguity and solving complex problems collaboratively
- Pragmatic, adaptable, and outcome-focused
- Strong communicator who builds trust quickly with clients and teammates
- Low-ego collaborator who enjoys working as part of multidisciplinary teams
- Inquisitive self-starter with attention to detail and a continuous drive to explore modern machine learning tooling
- Able to articulate technical trade-offs effectively to both technical peers and non-technical business partners

Qualifications
- Not essential but desirable: A degree (BSc, MSc, or PhD) in Computer Science, Data Science, Engineering, or an equivalent technical field
- At least three years of professional experience as a Machine Learning Engineer or Data Engineer
- Strong appreciation of commercial KPIs and experience aligning technical model performance with broader business objectives