Machine Learning Engineer Intern

London, United Kingdom

Applications have closed

Utility Warehouse

Get all your home services, including gas, electricity, broadband, mobile and home insurance from one company, helping you save time and money.

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Company Description

Hours: 9am to 5:30pm Monday to Friday 

Contract length: 3-6 month internship 

This role is available for both Remote and or Hybrid working

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/hyrbrid 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.

 

Hello, we're UW

We’re a bunch of great people working together, solving problems and having fun. Together, we strive to find solutions to help the great people around us get on with the things that really matter in life.

How? It’s simple, we take the headache out of essential home services by providing them all in one place – energy, broadband, mobile, and even insurance.  That’s one provider, one account, one bill, and lots of savings.
We’re a truly unique FTSE 250 company with a business model that has real social impact at the heart of it. Being a part of the UW community you’ll join a working environment like no other - one where everyone matters - be it our customers, our partners or you, our people.

 

About the role

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.

What you’ll do

  • 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.

About you

  • 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.

What’s in it for you

  • Competitive Internship remuneration.
  • Mentors and teachers aplenty; with so many creative colleagues in one place there is always someone you can lean on for support and guidance.
  • Flexible working: We’ve got fully remote teams, onsite, early risers and late-night grinders, and parents on the school run. For us, it matters what we’re working on more than where/when.
  • Work / Life balance and no-meetings day that encourage you to improve your creativity

Apply here!  

If you think this is the role for you and want to be part of UW’s extraordinary growth, apply now.

Job Description

 

 

Additional Information

We provide equal opportunities, a diverse and inclusive work environment, and fairness for everyone. You are welcome to apply no matter your age, disability, gender, marriage or civil partnership status, pregnancy and maternity status, race, religion or belief, or sexual orientation.

Please note, if you are applying for a role which involves having access to personal data, you will be subject to a background check. Where checks are unsatisfactory or incomplete and/or a failure to reveal information relating to convictions that you are required to identify as part of the background checks, could lead to withdrawal of an offer of employment.

Tags: Computer Science Data analysis Data pipelines Engineering Keras Machine Learning Matplotlib ML models MLOps NLP NumPy Pandas Pipelines Python PyTorch Research Scikit-learn Statistics TensorFlow

Perks/benefits: Career development Flex hours Insurance Startup environment

Regions: Remote/Anywhere Europe
Country: United Kingdom
Job stats:  533  204  4

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