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- Tasks: Develop machine learning products from conception to deployment in a collaborative team.
- Company: Join an IoT innovator focused on sustainable technology and virtual energy infrastructure.
- Benefits: Enjoy competitive salary, generous leave, and a flexible hybrid work environment.
- Why this job: Be part of a passionate team delivering paradigm-changing technology with positive social impact.
- Qualifications: MSc/MSci in a quantitative field; strong Python and machine learning skills required.
- Other info: Flexible start date; hiring at various experience levels, including fresh graduates.
The predicted salary is between 36000 - 60000 £ per year.
Would you thrive in a fast-scaling business, solving novel problems in collaborative teams? Are you interested in developing machine learning products from conception to deployment? 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 and contribute to a sustainable future. 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. 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.
Flexible start date. This role is based in our London office, near Liverpool Street (hybrid in-office and work-from-home).
Experience Level: Hiring at a range of experience levels; 0-4 years of experience.
We are looking for:
- MSc/MSci in a highly quantitative field (Mathematics, Computer Science, Physics, etc)
- Strong knowledge of Python and appropriate Machine Learning libraries and frameworks
- Strong analytical and communication skills
- Experience using Machine Learning on large datasets
- Experience collating, cleaning and visualizing datasets
- Ability to work autonomously, conducting research and posing difficult questions in order to build scalable algorithmic solutions to hard problems from the ground up
- Enthusiasm to learn and contribute to a culture of learning
- Advantageous - PhD (in a highly quantitative field)
What we offer:
- Competitive salary
- Generous annual leave allowance, excellent benefits package including salary sacrifice car scheme
Machine Learning Engineer Researcher PhD employer: Knauf Energy Solutions
Contact Detail:
Knauf Energy Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Engineer Researcher PhD
✨Tip Number 1
Familiarise yourself with the latest trends in machine learning and IoT technologies. Being able to discuss recent advancements or case studies during your interview can demonstrate your passion and knowledge in the field.
✨Tip Number 2
Engage with the data science community by attending meetups, webinars, or conferences. Networking with professionals in the industry can provide insights into the role and may even lead to referrals.
✨Tip Number 3
Prepare to showcase your problem-solving skills through practical examples. Think of specific projects where you’ve applied machine learning techniques to solve complex problems, as this will highlight your hands-on experience.
✨Tip Number 4
Research our company’s mission and values thoroughly. Understanding how we aim to contribute to a sustainable future will allow you to align your answers with our goals during the interview process.
We think you need these skills to ace Machine Learning Engineer Researcher PhD
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in machine learning, software engineering, and any quantitative fields. Emphasise projects where you've worked with large datasets or developed algorithms.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company’s mission. Discuss how your background aligns with their needs, particularly your experience with Python and machine learning frameworks.
Showcase Your Projects: If you have worked on any relevant projects, include them in your application. Describe the challenges you faced, the solutions you implemented, and the impact of your work, especially in collaborative settings.
Highlight Your Soft Skills: Since the role requires collaboration and communication, make sure to mention your soft skills. Provide examples of how you've effectively communicated complex ideas or worked in teams to solve problems.
How to prepare for a job interview at Knauf Energy Solutions
✨Showcase Your Technical Skills
Be prepared to discuss your experience with Python and machine learning libraries. Bring examples of projects where you've applied these skills, especially those involving large datasets.
✨Demonstrate Problem-Solving Abilities
Expect questions that assess your analytical thinking. Be ready to explain how you approach complex problems and the methodologies you use to develop scalable solutions.
✨Highlight Collaborative Experience
Since the role involves working in a team, share examples of successful collaborations. Discuss how you’ve contributed to team projects and how you handle differing opinions or challenges within a group.
✨Express Your Intellectual Curiosity
Convey your eagerness to learn and grow in the field. Talk about recent developments in machine learning that excite you and how you stay updated with industry trends.
