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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 technology.
- Benefits: Competitive salary, equity options, flexible work patterns, 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 grow your career.
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, containerization, 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 employer: Reasonable Technology Limited
Contact Detail:
Reasonable Technology Limited Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Member of Technical Staff
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. We all know that sometimes it’s not just what you know, but who you know that can help you land that dream job.
✨Tip Number 2
Show off your skills! Create a portfolio or GitHub repository showcasing your projects and experiments. We want to see your hands-on experience with machine learning and programming, so let your work speak for itself!
✨Tip Number 3
Prepare for those interviews! Brush up on your technical knowledge and be ready to discuss your past experiences. We love candidates who can articulate their thought process and demonstrate their problem-solving skills.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets noticed. Plus, we’re always on the lookout for passionate individuals ready to join our compact, talent-dense team in Budapest or London.
We think you need these skills to ace Member of Technical Staff
Some tips for your application 🫡
Show Your Passion: When you're writing your application, let your enthusiasm for machine learning and formal methods shine through. We want to see that you’re genuinely excited about the work we do and how you can contribute to our mission of developing superhuman programming AI.
Tailor Your CV: Make sure your CV highlights relevant experience and skills that align with the job description. Focus on your expertise in machine learning or formal methods, and don’t forget to mention any hands-on experience with MLOps tools or large language models. We love seeing how your background fits with our goals!
Craft a Compelling Cover Letter: Your cover letter is your chance to tell us why you’re the perfect fit for the role. Share specific examples of your past work, especially any projects that involved running machine learning experiments or using AI-assisted programming. Keep it engaging and personal – we want to get to know you!
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 at StudySmarter!
How to prepare for a job interview at Reasonable Technology Limited
✨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 experience running machine learning experiments and how you've tackled complex programming challenges. This is your chance to show off your knowledge!
✨Show Your Curiosity
Demonstrate your interest in learning the other domain if your expertise lies in one area. Talk about any relevant projects or experiences where you’ve had to pick up new skills quickly. Companies love candidates who are eager to grow and adapt!
✨Get Technical
Familiarise yourself with software engineering best practices and MLOps tools. Be prepared to discuss advanced git workflows, testing, and containerization. If you have experience with AI-assisted programming tools, make sure to highlight that too!
✨Ask Insightful Questions
Prepare thoughtful questions about the company's approach to post-human software engineering and their vision for the future. This shows you're genuinely interested in their work and helps you assess if it’s the right fit for you.
