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- Tasks: Design and develop innovative machine learning models for complex scientific data.
- Company: Join a pioneering deep tech startup with ambitious goals.
- Benefits: Competitive salary, equity package, and flexible remote work options.
- Other info: Collaborate with scientists and enjoy real ownership in your work.
- Why this job: Be a key player in shaping the future of analytical platforms.
- Qualifications: STEM degree and strong Python skills; curiosity is a must!
The predicted salary is between 50000 - 70000 £ per year.
Build the Models. Shape the Platform. Redefine What’s Possible. We’re working with an early-stage deep tech company developing a next-generation analytical platform at the intersection of machine learning, mathematics, and experimental science. They’re now hiring one of their first technical team members, a Machine Learning Research Engineer, to help design and develop the core ML-driven analysis engine that underpins the entire platform. This is not a narrow modelling role. It’s an opportunity to help define the research direction, shape the technical foundations, and influence how the platform evolves from day one. You’ll work closely with scientific leadership to translate complex experimental challenges into robust mathematical models and scalable software systems.
What You’ll Be Doing
- Designing novel algorithmic and machine learning approaches to interpret complex scientific data
- Developing mathematical models (including probabilistic / Bayesian methods)
- Building proof-of-concept tools and production-ready Python systems
- Managing and improving data pipelines from experimental instrumentation
- Continuously evaluating, refining, and stress-testing models
- Collaborating with scientists to solve emerging analytical challenges
This is a hands-on research-meets-engineering role with real ownership and technical depth.
What They’re Looking For...
Essential
- STEM degree (undergraduate or above)
- Strong Python software engineering skills
- Comfort working with mathematical modelling and statistical methods
- Intellectual curiosity and willingness to explore new approaches
Nice to Have
- Experience in machine learning (research or applied)
- Probabilistic modelling or Bayesian methods
- Exposure to scientific or experimental datasets
- Interest in biology, chemistry, physics, or drug discovery
Candidates at a range of levels will be considered, from exceptional recent graduates to PhD or industry-experienced researchers. The level of ownership and autonomy will reflect your experience.
Why This Role?
- Be one of the first technical hires in a high-ambition deep tech startup
- Genuine influence over architecture and research direction
- Direct collaboration with experienced scientific leadership
- Competitive salary aligned to experience
- Meaningful equity package
- Flexible / remote-friendly working
If you’re looking for a role where you can take responsibility, build from first principles, and apply machine learning to genuinely complex scientific problems, this could be your next move. We’re committed to creating an inclusive environment where everyone feels valued and respected. We welcome applications from people of all backgrounds, experiences, and perspectives. What matters most is your ability, curiosity, and drive to push technical boundaries.
Machine Learning Research Engineer ID46889 in Preston employer: Humand Talent
Contact Detail:
Humand Talent Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Machine Learning Research Engineer ID46889 in Preston
✨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 machine learning and data analysis. 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 problem-solving skills. Practice coding challenges and be ready to discuss your thought process. Remember, they want to see how you tackle complex problems!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Machine Learning Research Engineer ID46889 in Preston
Some tips for your application 🫡
Show Your Passion for Machine Learning: When writing your application, let your enthusiasm for machine learning shine through! Share specific examples of projects or experiences that sparked your interest in the field. We want to see your intellectual curiosity and how it aligns with our mission.
Tailor Your Application: Make sure to customise your CV and cover letter for this role. Highlight your Python skills and any experience with mathematical modelling or statistical methods. We’re looking for candidates who can directly relate their background to the challenges we face, so don’t hold back!
Be Clear and Concise: Keep your application straightforward and to the point. Use clear language to describe your experiences and skills. We appreciate well-structured applications that make it easy for us to see how you fit into our team and the exciting work we’re doing.
Apply Through Our Website: We encourage you to submit your application through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it shows you’re serious about joining our team at this innovative deep tech startup!
How to prepare for a job interview at Humand Talent
✨Know Your Algorithms
Brush up on your understanding of various machine learning algorithms, especially those relevant to probabilistic and Bayesian methods. Be ready to discuss how you would apply these techniques to real-world scientific data challenges.
✨Showcase Your Python Skills
Prepare to demonstrate your Python programming abilities. Bring examples of past projects or code snippets that highlight your software engineering skills, particularly in building scalable systems and managing data pipelines.
✨Emphasise Collaboration
This role involves working closely with scientists, so be prepared to discuss your experience in collaborative environments. Share examples of how you've successfully translated complex problems into actionable solutions through teamwork.
✨Demonstrate Intellectual Curiosity
Express your enthusiasm for exploring new approaches and methodologies. Be ready to discuss any recent trends in machine learning or experimental science that excite you, and how you might apply them in this role.