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- Tasks: Design and develop cutting-edge machine learning models with high autonomy.
- Company: Stealth-mode AI lab backed by top investors and tech leaders.
- Benefits: Competitive salary, equity, 28 days holiday, and professional growth opportunities.
- Other info: Collaborate with industry experts and tackle real-world challenges.
- Why this job: Join a pioneering team and make an impact from day one in AI research.
- Qualifications: Experience in machine learning, Python, and cloud technologies.
The predicted salary is between 60000 - 84000 ÂŁ per year.
Team: Machine Learning
Location: London (On-site; Liverpool Street)
Employment Type: Full-time and Permanent
Remuneration: £70 – 90k Base Salary + Discretionary Bonus + Equity
We are a stealth-mode AI laboratory researching and developing Machine Learning models.
The founding team consists of Cambridge graduates and former engineers at Google, Meta, Bloomberg, Microsoft and Amazon. We are backed by prominent investors from the US and the UK, including institutional VC funds and C-level executives of global technology companies.
In this role, you will:
- Design, develop and train large multimodal machine learning models across all stages: pre-training, post-training, evaluations and inference.
- Work closely with clients to understand data and model architecture requirements for their business needs.
- Be given a high degree of autonomy and ownership over your work.
- Co-hire your future colleagues.
- Work closely with the founding team and contribute towards best practices, standards, and culture of the company.
What we are looking for:
- Research engineering: Industry experience in complex machine learning projects including data processing and training models in a distributed environment.
- LLMs: Understanding of LLM architectures, pre and/or post-training, evaluations and inference.
- Programming languages: Proficiency in Python using PyTorch/TensorFlow/JAX framework.
- Cloud-native technologies: Experience in developing and deploying in cloud platforms (e.g., AWS, GCP or Azure), an understanding of containerisation (e.g., Docker).
- Algorithms and data structures: Excellent understanding of core CS fundamentals, including common abstract data structures and algorithms with the ability to apply them to optimise production systems.
- Problem solving: Strong analytical problem-solving skills and attention to detail. You have the ability to break down complex problems into actionable tasks.
- Collaboration and communication: Excellent interpersonal and communication skills with a desire to learn.
We would like to acknowledge that almost no candidate checks every box – and that is perfectly fine. If you are passionate about data and enjoy solving complex challenges, we would love to hear from you.
Nice to have:
- Publications: At top-tier ML/CV/NLP conferences (NeurIPS, ICML, ICLR, CVPR, ICCV)
- Open-source: Contributions to and experience in open-source projects.
- Startup experience: Experience with a startup work environment and wider ecosystem.
Why join us?
- Work in an environment conducting cutting-edge research in AI.
- An official role title of “Founding Research Engineer” – make an impact on day one.
- Competitive salary, equity and benefits package.
- 28 days + public holidays allowance.
- Opportunities for professional growth and progression with your career.
- Work on challenging engineering problems that have a real impact on the industry.
- Work with high-profile customers and technology partners.
Graduate ML Research Engineer employer: Zettafleet
Contact Detail:
Zettafleet Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Graduate ML Research Engineer
✨Tip Number 1
Network like a pro! Reach out to people in the industry, especially those who work at companies you're interested in. A friendly chat can lead to insider info and even referrals.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your machine learning projects. Whether it's GitHub repos or a personal website, let your work speak for itself.
✨Tip Number 3
Prepare for interviews by brushing up on your problem-solving skills. Practice coding challenges and be ready to discuss your thought process. We want to see how you tackle complex issues!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love hearing from passionate candidates who are eager to join our team.
We think you need these skills to ace Graduate ML Research Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV is tailored to the role of Graduate ML Research Engineer. Highlight your experience with machine learning projects, programming languages like Python, and any cloud technologies you've worked with. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you're passionate about AI and how your background makes you a great fit for our team. Don’t forget to mention any relevant projects or experiences that showcase your problem-solving skills.
Showcase Your Projects: If you've worked on any interesting machine learning projects, make sure to include them in your application. Whether it's a personal project or something from your studies, we love seeing practical applications of your skills. Links to GitHub or publications are a bonus!
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you're genuinely interested in joining our team at StudySmarter!
How to prepare for a job interview at Zettafleet
✨Know Your ML Models
Make sure you brush up on your knowledge of machine learning models, especially large multimodal ones. Be ready to discuss your experience with pre-training, post-training, and evaluations. This will show that you understand the core responsibilities of the role.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled complex problems in your previous projects. Break down your thought process and highlight your analytical skills. This will demonstrate your ability to handle the challenges that come with the job.
✨Familiarise Yourself with Cloud Technologies
Since the role involves cloud-native technologies, make sure you can talk about your experience with platforms like AWS, GCP, or Azure. If you’ve worked with containerisation tools like Docker, be ready to discuss how you’ve used them in your projects.
✨Communicate Effectively
Practice your communication skills, as you'll need to collaborate closely with clients and colleagues. Be prepared to explain technical concepts in a way that's easy to understand. This will show that you can work well in a team and contribute to the company culture.