At a Glance
- Tasks: Lead AI projects, optimise systems, and write production code in a hands-on role.
- Company: Fast-scaling AI business with a global remote team and engineering-led culture.
- Benefits: Up to £185K salary, £60K equity, fully remote work, and direct access to the CTO.
- Other info: No CV needed; apply with your LinkedIn profile and enjoy low bureaucracy.
- Why this job: Join a dynamic team solving complex AI challenges and make a real impact.
- Qualifications: Strong Python/PyTorch experience and a background in production-scale ML/LLM systems.
The predicted salary is between 185000 - 185000 £ per year.
I'm working on a unique AI role with one of the fastest-scaling AI businesses in the world right now. Up to £185,000 base + roughly £60,000 equity, fully remote globally. There is no office. Around 80 people worldwide. The company has scaled from 0 to 50 million users in around 2 years and is now processing 3 BILLION LLM tokens daily across mostly self-hosted infrastructure.
This is not an “AI wrapper” business. The engineering challenges are difficult:
- inference optimisation
- latency at scale
- RAG/memory systems
- RLHF/fine-tuning
- moderation/alignment systems
They’re looking for a very hands-on AI Tech Lead who still enjoys building systems and writing production code. Strong experience with Python/PyTorch, vLLM, Hugging Face and production-scale ML/LLM systems is essential.
The sort of person likely to fit this role:
- has shipped AI products used by millions
- understands production AI systems at scale
- values shipping quickly and pragmatically
- enjoys ownership and autonomy
Small senior AI team, direct access to the CTO, low bureaucracy and a very engineering-led culture. Most people in the business have come from very successful startups or Tier 1 companies like Palantir, Meta and Anthropic, or companies with an outstanding engineering pedigree like Deel.
This role is open to anyone across the EU, and the company will pay in your local currency. For the ease of my network, the role is advertised in pounds, but the same salary would be paid out in euros etc. £185K is roughly €215K, you get the idea.
No CV needed at this stage. Feel free to apply with your LinkedIn profile and we can cross the CV bridge later.
Lead LLM Engineer in Cambridge employer: Tact
Join one of the fastest-scaling AI businesses globally, where you can thrive in a fully remote environment with a competitive salary of up to £185K plus equity. With a strong engineering-led culture and minimal bureaucracy, you'll have direct access to the CTO and the opportunity to work alongside a talented team from top-tier companies, fostering both personal and professional growth in a dynamic and innovative setting.
StudySmarter Expert Advice🤫
We think this is how you could land Lead LLM Engineer in Cambridge
✨Tip Number 1
Make sure your LinkedIn profile is top-notch! Highlight your experience with Python, PyTorch, and any AI products you've shipped. This is your chance to showcase your skills without a CV, so let your profile do the talking.
✨Tip Number 2
Network like a pro! Reach out to connections in the AI space or those who work at companies you admire. A friendly chat can lead to valuable insights and even referrals, so don’t be shy!
✨Tip Number 3
Prepare for interviews by brushing up on the engineering challenges mentioned in the job description. Think about how you would tackle inference optimisation or latency at scale, and be ready to share your thoughts during the interview.
✨Tip Number 4
Apply through our website! It’s quick and easy, and we love seeing candidates who take the initiative. Plus, it gives us a chance to get to know you better right from the start.
We think you need these skills to ace Lead LLM Engineer in Cambridge
Some tips for your application 🫡
Show Your Passion for AI:When you're writing your application, let your enthusiasm for AI shine through! We want to see how your experience aligns with the challenges we face, like inference optimisation and RLHF. Make it personal and relatable!
Highlight Relevant Experience:Focus on your hands-on experience with Python, PyTorch, and production-scale ML systems. We’re looking for someone who has shipped AI products used by millions, so don’t be shy about showcasing your achievements in this area!
Keep It Concise and Clear:We appreciate clarity! Make sure your application is easy to read and straight to the point. Avoid jargon unless it’s relevant to the role. Remember, we want to understand your skills and experiences without wading through fluff.
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. Plus, you can use your LinkedIn profile, so no need to stress about a CV just yet!
How to prepare for a job interview at Tact
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, like Python, PyTorch, and Hugging Face. Brush up on your knowledge of production-scale ML/LLM systems and be ready to discuss your hands-on experience with them.
✨Showcase Your Problem-Solving Skills
Prepare to talk about specific engineering challenges you've faced, especially around inference optimisation and latency at scale. Use examples from your past work to demonstrate how you tackled these issues and what impact your solutions had.
✨Emphasise Ownership and Autonomy
This role values quick shipping and ownership, so be ready to share instances where you took charge of a project or feature. Highlight how you enjoy working independently and making decisions that drive results.
✨Cultural Fit is Key
Research the company culture and be prepared to discuss how your background aligns with their engineering-led environment. Mention any experiences from startups or high-performing teams that showcase your adaptability and collaborative spirit.
