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- Tasks: Join a cutting-edge team developing superhuman programming AI and innovative training methods.
- Company: Reasonable, an applied research company at the forefront of AI development.
- Benefits: Competitive salary, equity options, flexible working, and comprehensive health benefits.
- Why this job: Be part of a talent-dense team shaping the future of software engineering.
- Qualifications: Expertise in machine learning or formal methods, with a passion for learning.
- Other info: Exciting opportunity to relocate to Budapest or London and make a real impact.
The predicted salary is between 36000 - 60000 £ per year.
Reasonable is an applied research company developing training paradigms for superhuman programming AI. We draw on domain expertise in machine learning, formal verification and mathematical models of program semantics to create open-ended training environments, pre-training datasets, and post-training methods that continue to challenge LLMs even as they develop deeply superhuman levels of understanding and skill in programming. We think when AI writes most code, it will ultimately enable new ways for computers to be programmed, using programming paradigms that are just too challenging for humans to use at scale, enabling optimisations that were previously too complex to attempt. We call these applications post-human software engineering.
We aim to create a compact, talent-dense technical team to develop the next generation of frontier training methods. We want to build in Europe, have impact in the Bay Area. We prioritise applicants interested in relocating to Budapest or London.
Requirements
- Domain expertise in either machine learning or formal methods; interest in learning the other if expertise is in one of these
- Fast learning of deep technical subjects
- Experience running machine learning experiments, ideally at scale
- Experience with post-training large language models
- Knowledge of software engineering best practices (advanced git workflows, testing, containerisation, code reviews, etc)
- Familiarity with MLOps tools, working models on multi-GPU clusters
- An understanding of specification-aware programming (Dafny, Viper) and proof assistants (LEAN, Isabel)
- Experience using AI-assisted or AI-accelerated programming (Cursor or similar) and/or a willingness and ability to learn and grow in any of the above areas and beyond.
Benefits
- Competitive salary
- Equity (through share option scheme)
- Flexible working patterns
- Healthcare, childcare, fitness and other common benefits (we're figuring this out)
- Being there from the very early stages
Member of Technical Staff in London employer: Reasonable AI
Contact Detail:
Reasonable AI Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Member of Technical Staff in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, especially those who work at Reasonable or similar companies. A friendly chat can open doors and give you insights that might just land you an interview.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to machine learning or formal methods. This is your chance to demonstrate your expertise and passion for the field.
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of software engineering best practices and MLOps tools. Practice coding challenges and be ready to discuss your past experiences with machine learning experiments.
✨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, we love seeing candidates who are genuinely interested in joining our team.
We think you need these skills to ace Member of Technical Staff in London
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the job description. Highlight your domain expertise in machine learning or formal methods, and don’t forget to mention any relevant projects or experiments you've run.
Craft a Compelling Cover Letter: Your cover letter is your chance to show us your personality and passion for the role. Explain why you’re interested in working with us at Reasonable and how your background makes you a great fit for the team.
Showcase Your Technical Skills: We want to see your technical prowess! Include specific examples of your experience with machine learning experiments, software engineering best practices, and any familiarity with MLOps tools. This will help us understand your capabilities better.
Apply Through Our Website: Don’t forget to apply through our website! It’s the easiest way for us to keep track of your application and ensures you’re considered for the role. Plus, we love seeing candidates who take the initiative to follow our process.
How to prepare for a job interview at Reasonable AI
✨Know Your Stuff
Make sure you brush up on your domain expertise, whether it's machine learning or formal methods. Be ready to discuss your past experiences running machine learning experiments and how you've tackled complex programming challenges.
✨Show Your Curiosity
Demonstrate your eagerness to learn about the other area of expertise if you're strong in one. Ask insightful questions about their training paradigms and express your interest in expanding your knowledge in software engineering best practices.
✨Get Technical
Be prepared to dive deep into technical discussions. Familiarise yourself with MLOps tools and multi-GPU clusters, and be ready to talk about your experience with AI-assisted programming tools like Cursor. This will show that you’re not just a theorist but someone who can apply their knowledge practically.
✨Cultural Fit Matters
Understand the company's mission and values. Since they aim to build a compact, talent-dense team, convey your enthusiasm for being part of a small, impactful group. If you're open to relocating to Budapest or London, make sure to mention it!
