At a Glance
- Tasks: Develop and implement advanced AI systems while collaborating with top researchers.
- Company: Exciting YC-backed start-up at the forefront of AI technology.
- Benefits: Competitive salary up to £150,000 plus equity and on-site work in London.
- Other info: Dynamic environment with opportunities for significant career growth.
- Why this job: Join a world-class team and tackle complex challenges in machine learning.
- Qualifications: Degree in a quantitative field and strong Python software engineering skills.
The predicted salary is between 150000 - 150000 £ per year.
I'm currently working with a well-funded, high-growth AI company that is building cutting-edge technology at the intersection of machine learning, large-scale data systems, and applied research. They're looking for a Research Engineer to help bridge the gap between research and production, taking novel ideas from concept through to deployment and working on complex technical challenges alongside a world-class team.
What they're looking for:
- Degree in a highly quantitative subject such as Mathematics, Computer Science, Physics, Engineering, Statistics, Economics, or a related field from a leading university
- Strong software engineering skills, particularly with Python
- Experience building scalable systems and deploying machine learning models into production
- Ability to work across research and engineering, turning theoretical concepts into practical solutions
- Strong problem-solving skills and a track record of tackling complex technical challenges
What you'll be doing:
- Developing and implementing advanced machine learning and AI systems
- Working closely with researchers to productionise new algorithms and models
- Building scalable infrastructure, tooling, and data pipelines
- Conducting experiments and analysing results to drive product and technical decisions
- Collaborating with a highly technical team to solve challenging real-world problems
Package:
- Up to £150,000 base salary (depending on experience)
- Meaningful equity package
- London-based role (5 days per week on-site)
- Opportunity to work on genuinely cutting-edge technology alongside exceptional engineers and researchers
If you're interested in hearing more, please apply or send me a direct message.
Research Engineer - London - YC-backed Start-up employer: Oliver Bernard
Join a dynamic and innovative AI start-up in London, where you'll be at the forefront of developing cutting-edge technology that bridges research and production. With a strong emphasis on collaboration and problem-solving, this company offers a vibrant work culture, meaningful equity opportunities, and the chance to work alongside exceptional engineers and researchers on complex technical challenges. Embrace your potential for growth in a supportive environment that values creativity and innovation.
StudySmarter Expert Advice🤫
We think this is how you could land Research Engineer - London - YC-backed Start-up
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with current employees at the company. A personal introduction can make all the difference in landing that interview.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects, especially those related to machine learning and AI. This gives you a chance to demonstrate your expertise beyond just your CV.
✨Tip Number 3
Prepare for technical interviews by practicing coding challenges and system design problems. Use platforms like LeetCode or HackerRank to sharpen your skills and get comfortable with the types of questions you might face.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, it shows you’re genuinely interested in joining our team.
We think you need these skills to ace Research Engineer - London - YC-backed Start-up
Some tips for your application 🫡
Show Off Your Skills:Make sure to highlight your strong software engineering skills, especially with Python. We want to see how you can bridge the gap between research and production, so don’t hold back on showcasing your experience in building scalable systems.
Tailor Your Application:Take a moment to tailor your application to the job description. Mention your degree in a quantitative subject and any relevant experience you have with machine learning and AI systems. This helps us see how you fit into our world-class team.
Be Problem-Solving Savvy:We love candidates who can tackle complex technical challenges. Share specific examples of how you've solved problems in past projects. This will give us insight into your thought process and problem-solving skills.
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. We can’t wait to hear from you!
How to prepare for a job interview at Oliver Bernard
✨Know Your Stuff
Make sure you brush up on your knowledge of machine learning and AI systems. Be ready to discuss your experience with Python and any projects where you've built scalable systems or deployed models into production. This is your chance to show off your technical skills!
✨Showcase Problem-Solving Skills
Prepare to talk about specific challenges you've faced in previous roles and how you tackled them. Think of examples that highlight your ability to bridge the gap between research and engineering, as this is key for the role.
✨Ask Insightful Questions
Come prepared with questions that demonstrate your interest in the company and its technology. Ask about their current projects, the team dynamics, or how they approach turning theoretical concepts into practical solutions. This shows you're genuinely interested in contributing.
✨Be Ready to Collaborate
Since you'll be working closely with a highly technical team, be prepared to discuss how you collaborate with others. Share examples of past teamwork experiences, especially those involving complex technical challenges, to illustrate your ability to work well in a team setting.
