Machine Learning Research Engineer

Knauf Energy Solutions; City Of London; Hybrid; GBP 60,000 - 100,000; Full time

Benefits offered by this job

Salary sacrifice car scheme

Generous annual leave

Job summary

Knauf Energy Solutions is seeking a Machine Learning Research Engineer in London to develop novel algorithms for green-field problems within the Data Science and AI Team.

You will tackle large, complex datasets, balancing theory and deployment; collaborate across Europe in a fast-scaling IoT energy software business with positive environmental impact.

Qualifications

• MSc/MSci/PhD in a quantitative field (Maths, CS, Physics, etc).
• Strong Python skills and ML libraries/frameworks.
• Ability to autonomously conduct research and build scalable algorithms.
• Solid ML and statistics knowledge, including neural networks.
• Strong software engineering fundamentals.
• Enthusiasm to learn and contribute to a learning culture.
• Advantageous: PhD in a quantitative field.

Responsibilities

• Research and develop novel ML algorithms for difficult green-field problems.
• Design products from conception to deployment with practical rollout in mind.
• Collaborate with a Data Science and AI team across Europe.
• Work with large, complex datasets and ensure ethical considerations.

Skills

Python

Machine Learning

Statistics

Software Engineering

Autonomous research

Problem solving

Education

MSc/MSci/PhD in Mathematics, Computer Science, Physics, etc

Tools

Python libraries

ML frameworks

Job description

Would you thrive in a fast-scaling business, solving novel problems in collaborative teams? Are you interested in developing machine learning models for difficult green-field problems? If so, you could be the person we are searching for.

We are an IoT innovator working to scale our product deployments across the UK and EU. We are passionate about developing technology that will change paradigms, contribute to a sustainable future, and improve lives. We are building Virtual Energy Infrastructure using our world-leading machine learning algorithms.

We’re looking for a Machine Learning Research Engineer to work with us in our Data Science and AI Team. In this team, we build custom algorithms that use novel approaches to solve our business needs. This isn’t a prompt engineering or LLM role - finding a solution to our problems requires a deep understanding of Machine Learning, software development, and the problems themselves. You will be working with large, complex, and unique datasets to solve a wide range of difficult statistical, mathematical, and physical engineering problems.

To achieve this, you will work with cutting-edge technologies in a highly collaborative environment. Key to this role is the ability to envision and design new algorithm products while carefully considering the practicality of rollout, wider strategic implications, and any legal or ethical considerations – and then taking these products from conception to deployment.

This will require strong software engineering expertise and excellent machine learning proficiency. The ideal candidate brings not just technical skills, but an intellectual curiosity and eagerness to expand their knowledge across diverse technical domains.

You will be working with an enthusiastic, agile and highly skilled team to deliver a paradigm-changing technology across Europe with a positive environmental and social impact. Our world-leading algorithmic products are at the core of our business, so as a part of the Data Science and AI Team, you will have a high level of exposure to the wider business.

This role is based in our London office at Liverpool Street (hybrid in-office and work-from-home).

Experience Level:

• Hiring at a range of experience levels; 0-5 years of experience

We are looking for:

• MSc/MSci/PhD in a highly quantitative field (Mathematics, Computer Science, Physics, etc)
• Strong knowledge of Python and appropriate Machine Learning libraries and frameworks
• Ability to work autonomously to conduct research and pose difficult questions in order to build scalable algorithmic solutions to hard problems from the ground up
• Strong Machine Learning and Statistics knowledge; both in classical models and neural-network-style models
• Strong Software Engineering fundamentals
• Enthusiasm to learn and contribute to a culture of learning
• Advantageous- PhD (in a highly quantitative field)

What we offer

• Generous annual leave allowance, excellent benefits package including salary sacrifice car scheme