Machine Learning Engineer

Salary: £59,000 - 99,000 per year

Requirements:

• We are looking for experienced Machine Learning Engineers who are passionate and dynamic, with a strong interest in building production ML solutions and contributing to our growth.
• We require an advanced degree in computer science, mathematics, physics, engineering, or a related STEM field.
• You should have strong problem-solving skills and a solid grounding in classical machine learning and deep learning, from applied statistics and traditional ML algorithms to transformers and state-of-the-art deep learning.
• You need excellent collaboration and communication skills, both within teams and in client-facing engagements.
• You should be interested in building AI applications, including forecasting tools, image recognition applications, and LLM-based chatbots and agents.
• You must have proven ability to build machine learning models and pipelines using Python and common ML/DL libraries such as PyTorch or TensorFlow from early conceptualisation through to full deployment in scalable production environments.
• You should be able to design, deploy, and maintain ML solutions on modern frameworks, with adherence to software engineering best practices and exposure to version control, testing, MLOps, CI/CD, and API design.
• You must have hands-on experience using one of the three major cloud technologies, AWS, Azure, or GCP, in a production environment, as well as ML platforms such as AWS SageMaker or Azure Machine Learning Studio.
• You should be a lifelong learner with a drive to continually develop your own skills and help develop the skills of others around you.

Responsibilities:

• Define and implement machine learning projects across the full lifecycle, from conception and data preparation through model engineering, evaluation, deployment, monitoring, and maintenance.
• Establish and develop MLOps frameworks and standards for our clients and embed them within their infrastructure.
• Work with clients to upskill their teams, keep them informed throughout the project, and ensure they can take ownership after we roll off.
• Perform maturity assessments across clients cloud and AI environments and recommend improvements.
• Build ML strategy blueprints and advise clients on technology options.
• Translate business requirements, both functional and non-functional, into solutions that align with organisational strategy, policies, and standards.
• Help clients define new policies, philosophies, and standards where needed.
• Help clients identify risks and mitigations for ML and data science programmes, including transitions from on-premises to modern cloud-based infrastructures such as AWS, Azure, and GCP.
• Work with clients on ML model governance, including philosophies around fairness, transparency, interpretability, and accountability.

Technologies:

• AI
• API
• AWS
• Azure
• CI/CD
• Cloud
• GCP
• LLM
• Machine Learning
• MLOps
• PyTorch
• Python
• TensorFlow
• Support
• LESS

More:

We are Baringa, a global consulting firm that partners with leaders to drive change and create value. We bring deep industry expertise and advanced technology to help clients deliver with greater confidence and certainty. Our team of over 2,000 people works across the UK, Europe, North America, Asia, and Australia, combining global insight with local understanding. We operate across energy and resources, financial services, government and public sector, consumer products and retail, pharmaceuticals and life sciences, manufacturing, and technology, media and telecoms. Our Solutions and AI Lab team builds state-of-the-art AI solutions for clients, including forecasting tools, image recognition software, and genAI-powered applications. We are a certified Great Place to Work and have been recognised by the Financial Times and Forbes for our consulting excellence. We offer an inclusive recruitment process and encourage applications from candidates with diverse backgrounds and alternative career paths.

last updated 36 week of 2026