At a Glance
- Tasks: Design and deploy cutting-edge AI and machine learning models in drug development.
- Company: Innovative company at the forefront of drug manufacturing and AI technology.
- Benefits: Flexible working arrangements, ownership of projects, and career growth opportunities.
- Other info: Collaborative environment with cross-functional teams and a focus on responsible AI practices.
- Why this job: Shape the future of AI in healthcare while making a real-world impact.
- Qualifications: PhD in relevant field with 2-5 years of ML/AI experience and strong Python skills.
The predicted salary is between 50000 - 70000 € per year.
Nottingham – Flexible working arrangements. We are working with a company at the forefront of drug development and manufacturing. They turn drugs into usable forms, test them in humans, and manufacture the drugs. The company is now focused on investing in the Machine Learning and Artificial Intelligence space, and have several open positions in this area, so the team will be growing.
As an AI/ML Engineer, you’ll be involved across the full AI lifecycle - from getting the data in, through to building and deploying models, right through to monitoring how they perform in production. Internally, you’ll be seen as a go-to technical expert, helping to ensure best practices around responsible AI, model governance, and compliance are followed. You’ll also work cross-functionally with departments across the business from product managers to data engineers, to turn requirements into real-world AI solutions.
Key Responsibilities:- Design, develop, and deploy AI and machine learning models, finetune models as required.
- Build and maintain scalable ML pipelines and infrastructure for classical ML and deep learning.
- Deploy models to production using containerisation, CI/CD, and MLOps toolsets.
- Develop LLM-based tools using prompt engineering, retrieval, and embedding pipelines for knowledge retrieval and workflow assistance.
- Embed responsible AI practices and compliance in all solutions.
- Collaborate with cross-functional teams to translate requirements into technical solutions.
- Communicate complex technical concepts in clear terms to technical and non-technical stakeholders.
Ideally, you will have a PhD in a relevant field and 2-5 years’ experience in ML/AI engineering or data science roles in industry. An understanding of the drug development space is beneficial but not essential. You'll need to demonstrate a proven track record of building, deploying, and maintaining production-grade models. Strong coding skills in Python and ML frameworks (TensorFlow, PyTorch, Scikit-learn) are required. Experience with cloud platforms and ML infrastructure (ideally AWS but open to other cloud infrastructures, MLflow) is also necessary. Experience with LLMs, vector search, or retrieval-augmented systems is advantageous. Excellent communication skills are essential; you should be able to work cross-functionally with stakeholders of both technical and non-technical backgrounds.
This is a great opportunity for someone looking to take the next step in their career. You will get ownership and the chance to help shape a company’s AI and ML strategy while also putting it into practice. You’ll need to be self-motivated and enjoy the challenge of building things from scratch. Apply today to be considered.
Machine Learning Engineer in Nottingham employer: KEMIO Consulting
Join a pioneering company in Nottingham that is at the cutting edge of drug development and manufacturing, where you will have the opportunity to shape the future of AI and machine learning in healthcare. With flexible working arrangements, a collaborative work culture, and a commitment to employee growth, this role offers a unique chance to contribute to meaningful projects while developing your skills in a supportive environment. Be part of a team that values innovation and responsible AI practices, ensuring your work has a real-world impact.
StudySmarter Expert Advice🤫
We think this is how you could land Machine Learning Engineer in Nottingham
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to AI and ML. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice explaining complex concepts in simple terms, as you'll need to communicate effectively with both technical and non-technical folks.
✨Tip Number 4
Don't forget to apply through our website! We’re always on the lookout for talented individuals like you. Keep an eye on our open positions and make sure your application stands out!
We think you need these skills to ace Machine Learning Engineer in Nottingham
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Machine Learning Engineer role. Highlight your relevant experience, especially in AI/ML projects, and don’t forget to showcase your coding skills in Python and any ML frameworks you've worked with.
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background aligns with the company's focus on drug development. Keep it concise but impactful!
Showcase Your Projects:If you’ve got any personal or professional projects related to machine learning, make sure to mention them. Whether it's deploying models or building ML pipelines, real-world examples can really set you apart from other candidates.
Apply Through Our Website:We encourage you to apply through our website for the best chance of being noticed. It’s super easy, and you’ll be able to keep track of your application status directly!
How to prepare for a job interview at KEMIO Consulting
✨Know Your Stuff
Make sure you brush up on your machine learning concepts and frameworks like TensorFlow and PyTorch. Be ready to discuss your past projects in detail, especially those involving model deployment and maintenance. This will show that you’re not just familiar with the theory but have practical experience too.
✨Showcase Your Communication Skills
Since you'll be working with both technical and non-technical teams, practice explaining complex concepts in simple terms. Prepare examples of how you've successfully communicated technical information in the past, as this will demonstrate your ability to bridge the gap between different stakeholders.
✨Understand the Drug Development Space
While you don’t need to be an expert, having a basic understanding of drug development processes can set you apart. Research the company’s focus areas and think about how AI and ML can impact these processes. This knowledge will help you align your skills with their needs during the interview.
✨Prepare for Technical Questions
Expect to face technical questions or even coding challenges during the interview. Brush up on your Python skills and be prepared to solve problems on the spot. Practising common ML scenarios and algorithms can give you the confidence to tackle these questions effectively.
