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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 a 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 and opportunities for learning and growth in a dynamic environment.
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
Research Machine Learning Engineer (Hybrid) employer: Knauf Energy Solutions
Contact Detail:
Knauf Energy Solutions Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Machine Learning Engineer (Hybrid)
✨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, making you a standout candidate.
✨Tip Number 2
Engage with the data science community by attending meetups or webinars focused on machine learning and algorithm development. Networking with professionals in the field can provide insights into the role and may even lead to referrals.
✨Tip Number 3
Prepare to showcase your problem-solving skills by working on personal projects or contributing to open-source initiatives. Having tangible examples of how you've tackled complex datasets or developed algorithms will impress the hiring team.
✨Tip Number 4
Research StudySmarter's current projects and values, especially their focus on sustainability and innovation. Tailoring your conversation to align with our mission can show that you're not just looking for a job, but are genuinely interested in contributing to our goals.
We think you need these skills to ace Research Machine Learning Engineer (Hybrid)
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, as this aligns closely with the job requirements.
Craft a Compelling Cover Letter: In your cover letter, express your enthusiasm for the role and the company's mission. Discuss specific experiences that demonstrate your analytical skills and ability to work collaboratively on complex problems, as well as your eagerness to learn and grow within the field.
Showcase Technical Skills: Be sure to mention your proficiency in Python and any machine learning libraries you have used. If you have experience with data cleaning, visualisation, or deploying algorithms, include these details to strengthen your application.
Highlight Research Experience: If you have conducted research, particularly in a quantitative field, make it a focal point of your application. Discuss any challenges you faced and how you overcame them, as this demonstrates your problem-solving abilities and intellectual curiosity.
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 used these skills, especially with large datasets, to demonstrate your proficiency.
✨Demonstrate Problem-Solving Ability
Expect to face questions that assess your analytical thinking. Prepare to discuss how you've approached complex problems in the past, particularly in a collaborative setting, and how you envision developing scalable solutions.
✨Highlight Your Curiosity and Learning Mindset
Express your eagerness to learn and adapt. Share instances where you've pursued knowledge outside your immediate expertise, as this aligns with the company's culture of continuous learning and innovation.
✨Understand the Company’s Vision
Familiarise yourself with the company’s mission to create sustainable technology. Be ready to discuss how your values align with theirs and how you can contribute to their goal of making a positive environmental impact.
