At a Glance
- Tasks: Join us as a Research Engineer to design and implement cutting-edge AI systems.
- Company: Be part of a dynamic team shaping the future of autonomous technology.
- Benefits: Enjoy unlimited holidays, remote work options, and a competitive salary with equity.
- Why this job: Work on meaningful problems with a world-class team in a collaborative culture.
- Qualifications: Strong foundations in Machine Learning, Statistics, or Computer Science are essential.
- Other info: Hybrid work model with a vibrant office in London and monthly team events.
The predicted salary is between 36000 - 60000 £ per year.
About the Role
As a Research Engineer in the Core Intelligence team, you will actively contribute to the development of our autonomous system by contributing to the design and implementation of the system architecture, data curation, training and inference infrastructures, evaluation pipelines and alignment. You will operate at the cutting edge of AI, where there often isn’t any published research available, and be given the autonomy to explore novel methods.
You have a track record of excellence in your field and a desire to learn and perfect your craft. This is a real opportunity to witness the impact of your work without bureaucratic constraints.
You might be a good fit if you:
- enjoy wearing multiple hats, are results-oriented and can operate with loosely defined priorities
- have strong foundations in Machine Learning, Statistics and/or Computer Science that allows you to think from first principles
- are well-versed with the state of the art in AI and passionate about its future potential
- want to partner with world-class engineering and researchers to develop new autonomous capabilities
In this role, you will:
- research, design and implement experiments for finetuning and reinforcement learning on our autonomous system
- participate in the curation of datasets
- collaborate with the engineering team to productionize new iterations of the system
- drive the team’s research roadmap in collaboration with the rest of the technical staff
Where We Work
We work in a hybrid model where we meet in the office twice a week. We are currently hiring people who can physically be in London, but can make exceptions. Our office is in the City of London.
How We Work
Beyond the collaborative, open and transparent culture we strive to foster, there are a few things we strongly value.
- Speed and velocity are our unfair advantages. Moving fast and adapting does not mean delivering subpar work. Instead we focus on shipping and iterating on hypotheses as quickly as possible. Because done is better than perfect.
- Teamwork and ownership define us. We are here to do the best work of our lives at an individual level. The team is here to foster creative tension, constructive feedback and disagreement. While we all set a high bar for ourselves, we support and learn from each other by keeping one another accountable in an ego-less and respectful way.
- Solving problems, rather than building solutions. Idealists have a propensity to obsess over the solution. We are builders and innovators. We obsess over the problem, and find novel ways to solve it.
- Necessity begets creativity. The best ideas are born out of necessity. We constantly try to find ways to drive results with significantly fewer resources. Not only because we should, but because we have to.
- Work on hard and meaningful problems. You’d be working directly on shaping the future of software with AI with a world-class team.
- Competitive base salary and meaningful equity. We want to make sure you have skin in the game.
- Private WeWork office in brand new location in the City of London
- Unlimited holidays. Ability to work remotely for a set period of time each quarter as well.
- Equipment of your choice + WFH stipend. We have our own (physical) GPUs to run experiments with.
- Monthly team events, hackathons, conferences… We are builders and hackers at heart. We are creating the environment and culture for passionate and ambitious people to learn, share and connect. This is the fertile ground where the best ideas are born from.
How to Apply
Send an email to with your
- CV
- LinkedIn URL
- Github repo or website (if applicable)
- Answers to the following questions (in as few/as many words as you like)
- Why are you interested in joining?
- What are one personal and one professional/academic you are most proud of?
- (optional) Anything else you want us to know, such as your motivation to apply or additional context for your application.
Interview Process
Interviews will be focused on your area of expertise but also designed to see how you stretch beyond your comfort zone.
- Introductory call (45mins) with one co-founder
- Technical call (45mins) with a member of the team
- Take-home task. A research task with a clear objective which will be a reflection of what you’d work on at agemo.
- On-site interviews. After we assess your take-home task, you will be invited to present it to the team on site; this will be an opportunity to meet the team in person as well. There will be a final culture fit interview with a member of the team.
- Decision. You should expect to hear from us within a few days after the final interview with an offer or clear feedback.
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Research Engineer, Core Intelligence Member of Technical Staff London / Remote employer: Agemo
Contact Detail:
Agemo Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Research Engineer, Core Intelligence Member of Technical Staff London / Remote
✨Tip Number 1
Familiarize yourself with the latest advancements in AI and Machine Learning. Since this role involves working at the cutting edge of technology, being well-versed in current trends and methodologies will help you stand out.
✨Tip Number 2
Showcase your problem-solving skills during the interview process. Be prepared to discuss how you've tackled complex challenges in your previous work, as this aligns with our focus on solving problems rather than just building solutions.
✨Tip Number 3
Emphasize your ability to work collaboratively in a team environment. Highlight experiences where you've successfully partnered with others to achieve results, as teamwork and ownership are core values for us.
✨Tip Number 4
Prepare for the take-home task by practicing similar research projects. This will not only help you understand what is expected but also allow you to demonstrate your skills effectively when you present your work to the team.
We think you need these skills to ace Research Engineer, Core Intelligence Member of Technical Staff London / Remote
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in Machine Learning, Statistics, and Computer Science. Emphasize any projects or roles where you contributed to autonomous systems or AI research.
Craft Thoughtful Responses: When answering the application questions, be genuine and concise. Clearly articulate why you're interested in this role and how your personal and professional achievements align with the company's mission.
Showcase Your Work: If applicable, include links to your GitHub repository or personal website. Highlight projects that demonstrate your skills in AI and your ability to solve complex problems.
Prepare for Interviews: Anticipate questions related to your expertise and be ready to discuss how you approach problem-solving. Think about examples from your past work that showcase your ability to innovate and collaborate effectively.
How to prepare for a job interview at Agemo
✨Showcase Your Technical Expertise
Be prepared to discuss your experience in Machine Learning, Statistics, and Computer Science. Highlight specific projects where you've applied these skills, especially in areas related to autonomous systems or AI.
✨Demonstrate Problem-Solving Skills
During the interview, focus on how you approach problem-solving. Share examples of challenges you've faced in past projects and how you innovatively addressed them, emphasizing your ability to think from first principles.
✨Emphasize Collaboration and Teamwork
Since the role involves working closely with engineers and researchers, illustrate your experience in collaborative environments. Discuss how you’ve contributed to team dynamics and supported others in achieving common goals.
✨Prepare for the Take-Home Task
The take-home task is a critical part of the interview process. Approach it as if it were a real project: define clear objectives, document your methodology, and be ready to present your findings confidently during the on-site interviews.