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- Tasks: Work on cutting-edge AI models and solve real-world problems.
- Company: Dynamic tech firm in Central London with a focus on impactful research.
- Benefits: Attractive salary, collaborative environment, and rapid project turnaround.
- Other info: Join a small team where your contributions truly matter.
- Why this job: Make a tangible impact in AI with high ownership and innovative peers.
- Qualifications: Strong background in machine learning and problem-solving skills.
£220,000 – £280,000 base · On-site · Central London
Most AI research roles sit at one of two extremes - pure academia with little real-world impact, or pure engineering with little room to think. This one sits in the narrow band between them, where the work is serious, the models are live, and the problems are genuinely unsolved.
You'll work on the core model stack - post-training, fine-tuning, alignment, evaluation - and see the results in production within weeks, not quarters. The measure of success is model performance in the real world, not benchmark scores or citation counts.
Small team. High ownership. High-calibre peers.
WHAT YOU'LL WORK ON
- Post-training
Senior Research Engineer employer: DURLSTON PARTNERS
Contact Detail:
DURLSTON PARTNERS Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Research Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with fellow engineers 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 that demonstrate your experience with model performance and real-world applications. This will help you stand out when chatting with potential employers.
✨Tip Number 3
Prepare for interviews by brushing up on both technical and soft skills. Be ready to discuss your past experiences with post-training and fine-tuning models, and don’t forget to highlight how you’ve tackled unsolved problems in your previous roles.
✨Tip Number 4
Apply through our website! We’re always on the lookout for talented individuals who can contribute to our team. Plus, applying directly gives you a better chance of getting noticed by hiring managers.
We think you need these skills to ace Senior Research Engineer
Some tips for your application 🫡
Show Your Passion for AI: When you're writing your application, let your enthusiasm for AI and machine learning shine through. We want to see that you’re not just ticking boxes but genuinely excited about the challenges and innovations in this field.
Highlight Real-World Impact: Make sure to emphasise any projects or experiences where your work had a tangible impact. We’re all about seeing results in production, so share examples of how your contributions made a difference in real-world applications.
Tailor Your CV and Cover Letter: Don’t just send a generic CV! Tailor your application to reflect the specific skills and experiences that align with the Senior Research Engineer role. We love it when candidates take the time to connect their background to what we do.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at DURLSTON PARTNERS
✨Know Your Models Inside Out
Make sure you have a solid understanding of the core model stack, including post-training techniques and fine-tuning methods. Be prepared to discuss your previous experiences with real-world applications of these models and how you've tackled unsolved problems.
✨Showcase Your Problem-Solving Skills
During the interview, highlight specific examples where you've successfully aligned and evaluated models in production. Discuss the challenges you faced and how you overcame them, as this will demonstrate your ability to think critically and adapt in a fast-paced environment.
✨Emphasise Team Collaboration
Since you'll be working in a small team with high ownership, it's crucial to convey your experience in collaborative settings. Share instances where you've worked closely with peers to achieve common goals, and how you value input from others in the research process.
✨Prepare for Technical Questions
Expect technical questions that assess your knowledge of machine learning concepts and their practical applications. Brush up on recent advancements in AI and be ready to discuss how they can impact model performance in the real world. This shows you're not just knowledgeable but also passionate about the field.