Machine Learning Engineer

Arbeitsplatz

• Qualifikationslevel B Ausübungsformen

Gewünschte Fähigkeiten & Kenntnisse

Machine Learning API Cloud CAN LESS Solid Innovation Entwicklungsumgebungen MOST Policy Beratung SQL Azure Compliance Software-Engineering START across Forecasting Übersetzungssoftware AWS Python Hybrid TensorFlow Support Continuous Integration Engineering Flexibilität, * 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
• 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 (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)
• 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

• 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.
• Profit Share Scheme: All employees participate in the Baringa Group Profit Share Scheme so everyone has a stake in the company’s success. We are proud to be an Equal Opportunity Employer. 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. All applications will receive consideration for employment without regard to race, ethnicity, religion, gender, gender identity or expression, sexual orientation, nationality, disability, age, faith or social background. We do not filter applications by university background and encourage those who have taken alternative educational and career paths to apply. We would like to actively encourage applications from those who identify with less represented and minority groups. We operate an inclusive recruitment process, ensuring reasonable adjustments where needed. For UK & EU For the USA For Australia & Singapore #J-18808-Ljbffr

We set out to build the world’s most trusted consulting firm - creating lasting impact for clients and pioneering a positive, people-first way of working. We work with everyone from FTSE 100 names to bright new start-ups, in every sector.

You’ll 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. Our clients love how we get to know what makes their organisations tick - slotting seamlessly into their teams and being proudly geeky about solving their challenges.

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. Find us wherever there’s a challenge to be tackled and an impact to be made.

Our Solutions & AI Labs (SAIL) 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).

• 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