Machine Learning Engineer Language, London

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Youll find us collaborating shoulder-to-shoulder with our clients, from the big picture right down to the detail: helping them define their strategy, deliver complex change, spot the right commercial opportunities, manage risk, or bring their purpose and sustainability goals to life. We have hubs in Europe, the US, Asia and Australia, and we work all around the world - from a wind farm in Wyoming to a boardroom in Berlin. Our SAIL (Solutions and AI Lab) practice are looking for an experienced Machine Learning Engineer 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.
This expertise is applied across clients in all of our industry market sectors (Financial Services, Products & Services, Energy & Resources, Pharmaceutical & Lifesciences and Government).
Check out our ENA AI Platform Case Study to see how we accelerated low-carbon device roll-outs for the UK.
You will be using your experience to help our clients solve their most important data challenges. You would be also responsible to support the growth of our team, helping them to build the skills they need to solve our clients challenges. 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 and in some cases, help customers to define new policies, philosophies 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
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. Passionate person who is excited by problems within machine learning and can bring a good mix of technical delivery and core consulting skills in client engagements
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
Interested in building AI applications, ranging from forecasting tools to image recognition applications and LLM-based chatbots and agents
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 and with exposure to version control, testing, MLOps, CI/CD and API design
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)
We recognise the importance of work-life balance and flexible working and provide our staff amazing benefits. Generous Annual Leave Policy: We recognise everyone needs a well-deserved break. We provide our employees with 5 weeks of annual leave, fully available at the start of each year. In addition to this, we have introduced our 5-Year Recharge benefit which allows all employees an additional 2 weeks of paid leave after 5 years continuous service.
Flexible Working: We know that the ideal work-life balance will vary from person to person and change at different stages of our working lives. To accommodate this, we have implemented a hybrid working policy and introduced more flexibility around taking unpaid leave.
Corporate Responsibility Days: Our world is important to us, so all our employees get 3 every year to help social and environmental causes and increase our impact on the communities that mean the most to us.
Career Progression: Thats why we have quarterly rather than annual promotion reviews. We dont have any quotas: if youre ready and delivering at the right level, youll get that promotion.
Profit Share Scheme: All employees participate in the Baringa Group Profit Share Scheme so everyone has a stake in the companys success.
Diversity and Inclusion.
We believe that creating an environment where everyone feels a sense of belonging is central to our culture and that diversity is paramount to driving creativity, innovation, and value for our clients and for our people.
You can be a part of our Great Place to Work with our commitment to women and well-being in the workplace for all.
We maintain high standards of environmental performance and transparency, which can be seen through our commitment to Net Zero with our SBTI-verified Scope 1, 2 and 3 emissions reduction targets and our support of the Better Business Act. We report our progress publicly and ensure that we are also externally assessed and scored through organisations like CDP and EcoVadis - helping us to continually identify where we can improve.
We have a long legacy of supporting the communities in which we work, and offer a variety of ways to contribute, by putting people first and creating impact that lasts. Our Corporate Social Responsibility (CSR) agenda is about giving back to the communities in which we live and work by sharing our skills, talent and time.

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Location:: London
Job Type:: FullTime

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