Machine Learning Engineer Intern
- You will be part of the first summer internship in the Machine Learning area of Data at UW. This is a 3-month internship with a start date available from mid/late June, open to people who are in their penultimate year of education (undergraduate/postgraduate) or have recently graduated.
- This is a paid, fully-remote internship opportunity where you are able to develop experience as a Machine Learning Engineer in a growing company with a modern ‘data stack’. UW has a unique word-of-mouth business model via its Partner network but is complementing that through digital channels like paid search, retargeting and referral programmes.
- We are looking for a Machine Learning Engineering Intern to join our team. As a Machine Learning Engineering Intern, you will be responsible for assisting in the development and deployment of products based on machine learning models and algorithms to solve complex problems. You also have the opportunity to work on improving the MLOps framework and technology stack. You will work closely with our team of data scientists and machine learning engineers to design, implement and test new machine learning solutions. The ideal candidate will be passionate about machine learning, have strong programming skills, and be comfortable working in a collaborative team environment.
- Machine Learning Engineers at Utility Warehouse are expected to play a leading role and to enjoy the challenges that come from being the UK’s only multiservice utility provider. We are developing a diverse team of people who each bring their different strengths and approaches to our working community.
- Our mission with data is to create value and impact for Utility Warehouse through scaling AI and automation across our organisation. For example, we are exploring our ability to drive product growth through machine learning, understanding our customers’ needs and improving customer interactions with UW using natural language processing. We are also using machine learning models in our partners app to help equip our partners with the information they need to expand our customer base. Our exciting AI and machine learning journey is under way and we are looking for motivated individuals to join us.
Area of Responsibilities
- Designing and improving our MLOps Framework (ML tools, packages,.. ) and technology stack
- Developing the analytics and machine learning training and prediction infrastructure.
- Partnering with Data Scientists to develop and implement Machine Learning Models.
- Working with Software Engineering teams to define and develop best practices.
- Designing and building scalable, reliable and robust data pipelines to acquire, ingest, and process data from multiple sources.
- Data modelling - bringing a structure to raw data that is aligned with business requirements and objectives.
- Maintaining a product mindset - what needs to be improved next?
- Optimise machine learning algorithms for scalability and efficiency.
- Keep up to date with the latest research and developments in machine learning and related fields.
- Document and communicate results to technical and non-technical stakeholders.
- Contributing to cross-functional problem-solving sessions.
- Currently pursuing a degree in computer science, data science, statistics, or a related field.
- Experience with programming languages such as Python.
- Familiarity with machine learning libraries such as Sklearn, TensorFlow, Keras, or PyTorch.
- Experience with data analysis and visualisation tools such as Pandas, Numpy, or Matplotlib.
- Strong analytical and problem-solving skills.
- Ability to continually optimise and improve data pipelines.
- Strong interpersonal skills incorporating leadership, mentoring, team working, knowledge sharing and helping to create a positive culture.
- Ability to prioritise and organise own workload in coordination with the team and stakeholders.
- Huge opportunities for exposure & development as we scale up
- Access to Spark – a holistic approach to learning and development created by UW to empower our people's personal and professional growth
- Competitive salary including share options
- 25 days holiday plus Bank Holidays
- Life Insurance up to 4 x your salary
- Discounted healthcare & medical cash plans
- A free virtual GP service
- Private pension scheme
- Share options and Save As You Earn Scheme
- A range of Health & Wellbeing benefits including a confidential Employee Assistance Programme, virtual fitness classes and wellness tools
- Discounted UW services (30% mobile & broadband, 10% energy & insurance)
- A UW cashback card - earning you cashback on all your spending!