Location
London

Hours
Contract role - hours negotiable

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’ve partnered with clients to solve complex challenges, build high-performing teams, and create lasting capability.

As a Machine Learning Engineer, you will deploy and operate AI and machine learning architectures in production ecosystems. You will work on constructing high-volume batch processing systems, real-time microservices, automated continuous retraining, and system observability. You will architect sustainable machine learning solutions across the entire lifecycle without compromising key product outcomes.

This role requires collaboration with multidisciplinary teams, clear communication with clients and teammates, and a pragmatic, adaptable, outcome-focused approach. You will be encouraged to continuously learn and explore modern machine learning tooling while delivering high-quality work that drives real value.

Experience
- Hands-on experience deploying and operating AI and machine learning architectures in production
- Proficient in high-volume batch processing, real-time microservices, automated retraining, and system observability
- Strong technical foundations in Python and SQL
- Experience with modern modeling toolkits such as PyTorch, TensorFlow, and Scikit-learn
- Practical expertise with public cloud environments, preferably Google Cloud Platform technologies like BigQuery, Vertex AI, and Dataflow
- Skilled with deployment pipelines, version control, and containerization platforms such as Docker and Kubernetes
- Familiarity with advanced generative AI, Large Language Models, and agent orchestration tools such as ADK, LangChain, or AutoGen
- Ability to articulate technical trade-offs to both technical and non-technical stakeholders

About you
- You care deeply about producing high-quality work that delivers real value
- Comfortable navigating ambiguity and solving complex problems collaboratively
- Strong communicator who builds trust quickly with clients and teammates
- Pragmatic, adaptable, and outcome-focused
- Value low-ego collaboration and enjoy working as part of multidisciplinary teams
- Inquisitive self-starter with attention to detail and a continuous learning mindset

Qualifications
- Not essential but desirable: a degree (BSc, MSc, or PhD) in Computer Science, Data Science, Engineering, or an equivalent technical field
- Preferably 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