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.
We are focused on delivering value-adding solutions aligned to our client’s specific needs. This expertise is applied across clients in all of our industry market sectors (Financial Services, Products & Services, Energy & Resources, Pharmaceutical & Lifesciences and Government).
Curious what that impact looks like? Check out our to see how we accelerated low-carbon device roll-outs for the UK.
What you will be doing
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 client’s challenges. Typical engagements include:
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
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. We’re looking for people who can both advise our clients and get hands on in technical delivery to bring a solution to life.
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 Excellent collaboration and communication skills, both with teams and in client-facing engagements 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 ( 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 (, 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
We recruit individuals at all levels based on merit. Don’t worry about ‘fitting into a quota’ – if you’ve got the skills we are after we would love to talk to you.
What a career at Baringa will give you
Putting People First.
Baringa is a People First company and wellbeing is at the forefront of our culture. We recognise the importance of work-life balance and flexible working and provide our staff amazing benefits. Some of these benefits include:
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. Wellbeing Fund: We want to encourage all employees to take charge and prioritise their own wellbeing. We’ve introduced our annual People Fund to support this by offering every individual a fund to support and manage their wellbeing through an activity of their choice. Career Progression: No one develops at the same pace. That’s why we have quarterly rather than annual promotion reviews. We don’t have any quotas: if you’re ready and delivering at the right level, you’ll get that promotion. Profit Share Scheme: All employees participate in the Baringa Group Profit Share Scheme so everyone has a stake in the company’s success.
