At a Glance
- Tasks: Lead research on AI systems that think and learn over time.
- Company: Join a cutting-edge AI company focused on real-world impact.
- Benefits: Competitive salary, flexible work environment, and opportunities for growth.
- Other info: Collaborative team culture with a focus on high-quality work and rapid learning.
- Why this job: Shape the future of AI with innovative technologies and make a global difference.
- Qualifications: Proven experience in machine learning and a passion for building impactful systems.
The predicted salary is between 100000 - 150000 £ per year.
A1 is building a proactive AI system that goes beyond responding to prompts – it maintains context across conversations, plans actions, and carries work forward over time. You will own the research and intelligence direction of this system. Your role is to define how AI reasons, evaluates, and improves in a product used with high frequency.
What You'll Do
- Set and evolve the research direction for A1’s core intelligence, including context representation, memory, reasoning, planning, and orchestration.
- Decide when to design new model architectures versus adapting or leveraging frontier open-source or commercial models.
- Define evaluation frameworks that measure real-world usefulness, robustness, safety, and long-term behavior – not benchmark vanity.
- Own alignment, safety, and guardrail strategy as first-class product concerns.
- Guide exploration of frontier techniques such as:
- retrieval-augmented training
- mixture-of-experts
- distillation
- multi-agent orchestration
- multimodal systems
Requirements
- Deep experience building or evolving real machine learning systems used in production.
- Strong technical judgment around model behavior, failure modes, and long-horizon trade-offs.
- A builder’s mindset: you care about systems that work in the real world, not just ideas.
- Comfortable making irreversible or high-impact decisions with incomplete information.
- Obsession with evaluation, correctness, and how systems behave over time.
- High ownership mentality — you operate as a founder, not a manager.
- If you are looking to focus primarily on publishing, incremental benchmarks, or managing a large research organization, this role will not be a fit.
Tech Stack
- Python
- PyTorch / JAX
- GPU-based training and inference system
How We Work
The best products today in the world were built by small, world class teams. We are a high talent density and hands-on team. We make decisions collectively, move at rapid speed, striking a balance between shipping high quality work and learning. Joining our team requires the ability to bring structure, exercise judgment, and execute independently. Our goal is to put in hands of our users a truly magical product.
Interview process
If there appears to be a fit, we'll reach to schedule 3, but no more than 4 interviews. Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite. We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us. This isn't just a job offer; it's an invitation to be part of a team that's bringing AI to have practical benefits to billions globally.
VP of Research, Machine Learning in London employer: Bjak
Contact Detail:
Bjak Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land VP of Research, Machine Learning in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Prepare for those interviews! Research common questions for VP roles in machine learning and practice your responses. We recommend doing mock interviews with friends or using online platforms to get comfortable with the format.
✨Tip Number 3
Showcase your passion for AI! During interviews, share your thoughts on the latest trends and how they relate to A1’s mission. This will demonstrate your enthusiasm and alignment with their goals.
✨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 being part of our team.
We think you need these skills to ace VP of Research, Machine Learning in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience in machine learning systems. We want to see how your skills align with our mission at A1, so don’t hold back on showcasing relevant projects!
Showcase Your Technical Skills: Since we’re all about building real-world systems, include specific examples of your work with Python, PyTorch, or JAX. Let us know how you’ve tackled challenges in model behaviour and evaluation – we love a good story!
Be Clear and Concise: When writing your application, keep it straightforward. We appreciate clarity, so avoid jargon unless it’s necessary. Make it easy for us to see your qualifications and passion for the role without wading through fluff.
Apply Through Our Website: We encourage you to submit your application directly through our website. It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it shows you’re keen to join our team!
How to prepare for a job interview at Bjak
✨Know Your Stuff
Make sure you have a solid grasp of machine learning concepts, especially around context representation and reasoning. Brush up on your experience with Python, PyTorch, and JAX, as these are crucial for the role. Be ready to discuss specific projects where you've built or evolved real ML systems.
✨Show Your Builder's Mindset
Demonstrate your passion for creating systems that work in the real world. Share examples of how you've tackled challenges in previous roles, focusing on your decision-making process and how you approached high-impact decisions with incomplete information.
✨Emphasise Evaluation and Safety
Be prepared to talk about your obsession with evaluation frameworks and how you've ensured robustness and safety in your past projects. Discuss any experiences you have with alignment strategies and guardrails, as these are key concerns for the role.
✨Collaborative Spirit
Since the team values collective decision-making, highlight your experience working in high-talent teams. Share instances where you've collaborated closely with product and engineering teams to shape product intelligence direction, showcasing your ability to execute independently while still being a team player.