Machine Learning Engineer in London

About Baringa

Baringa is a global consulting firm that partners with leaders to drive change and create value. With deep industry expertise, and enabled by advanced technology, the firm helps clients to deliver with greater confidence and certainty. The firm works across energy and resources, financial services, government and public sector, consumer products and retail, pharmaceuticals and life sciences, manufacturing, and technology, media and telecoms, with capabilities spanning strategy, transformation and operational excellence – all powered by advanced technology, data, AI and digital innovation.

Our Solutions and AI Lab Team are looking for experienced Machine Learning Engineers to join the team. In SAIL, we build state-of-the-art AI solutions that help our clients with some of their biggest projects - ranging from tools that support energy networks forecast risk and adapt to climate change using empirically-derived resilience models, to image recognition software using satellite and aerial imagery, to genAI-powered applications including bespoke assistants and agents.

What you will be doing:

• Defining and implementing machine learning projects over the full lifecycle, from conception to data preparation, model engineering, evaluation and deployment and finally model monitoring and maintenance.
• Establishing and developing ML Ops frameworks and standards for clients and embedding within their infrastructure.
• Working with clients to take them on the journey, upskilling along the way and ensuring they are kept in the loop and can take ownership after you roll off the project.
• Performing maturity assessments across clients’ Cloud/AI environments and recommending improvements.
• Building ML strategy blueprints and advising clients on the different technology options.
• Translating business requirements (both functional and non-functional) into solutions, ensuring compliance with the organisations strategy, policies and standards.
• Helping clients to identify risks and mitigations for their ML and DS programmes, as well as transition from on-prem to modern cloud-based infrastructures (AWS, Azure, GCP).
• Working with clients in key areas of ML model governance, such as in defining philosophies including fairness, transparency, interpretability, and accountability.

Your Skills and Experience:

• We are seeking passionate and dynamic ML engineers who are excited by building production ML solutions, and keen to take an active part in the growth of the company.
• Advanced degree in computer science, mathematics, physics, engineering or related STEM field.
• Strong problem-solving skills and solid grounding in classical ML and deep learning: from applied statistics and traditional machine learning algorithms to transformers and SOTA deep learning.
• Excellent collaboration and communication skills, both with teams and in client-facing engagements.
• Proven ability to build machine learning models and pipelines using Python and common ML and DL libraries (e.g. Pytorch, Tensorflow) from early conceptualisation to full deployment in scalable production environments.
• Ability to design, deploy and maintain ML solutions on modern frameworks to meet functional business requirements, adhering to software engineering best practices.
• Hands on experience in using one of 3 major cloud technologies (AWS, Azure or GCP) in a production environment, as well as ML platforms (e.g., AWS Sagemaker, Azure Machine Learning studio).
• Be a ‘lifelong learner’ and can demonstrate a drive to always be learning and developing your skillsets and develop the skillsets of others around you.