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 Liverpool 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 Liverpool
✨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 open doors and give you insights that might just help you land that Lead LLM Engineer role.
✨Tip Number 3
Prepare for the interview by brushing up on the engineering challenges mentioned in the job description. Be ready to discuss your hands-on experience with inference optimisation and RLHF. Show them you’re not just a talker but a doer!
✨Tip Number 4
Don’t forget to apply through our website! It’s the easiest way to get your application noticed. Plus, we love seeing candidates who take the initiative to engage directly with us.
We think you need these skills to ace Lead LLM Engineer in Liverpool
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 excited you are about the challenges in the field and how you've tackled them in the past. Share specific examples that highlight your hands-on experience with production-scale ML/LLM systems.
Tailor Your LinkedIn Profile:Since you can apply with your LinkedIn profile, make sure it’s up-to-date and reflects your skills relevant to the role. Highlight your experience with Python, PyTorch, and any AI products you've shipped. We love seeing a clear connection between your background and what we’re looking for!
Be Concise and Clear:Keep your application straightforward and to the point. We appreciate clarity, so avoid jargon unless it’s necessary. Make it easy for us to understand your experience and how it aligns with the role of AI Tech Lead. Remember, less is often more!
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for the role. Plus, it gives you a chance to explore more about our company culture and values while you’re at it!
How to prepare for a job interview at Tact
✨Know Your Tech Inside Out
Make sure you’re well-versed in Python, PyTorch, and the other technologies mentioned in the job description. Brush up on your knowledge of LLM systems and be ready to discuss specific projects where you've implemented these technologies.
✨Showcase Your Problem-Solving Skills
Prepare to talk about the engineering challenges you've faced, especially around inference optimisation and latency at scale. Use concrete examples to demonstrate how you tackled these issues and what the outcomes were.
✨Emphasise Your Hands-On Experience
This role is all about being hands-on, so highlight your experience in building systems and writing production code. Share stories that illustrate your ownership and autonomy in previous roles, as this will resonate with their engineering-led culture.
✨Be Ready for a Technical Deep Dive
Expect technical questions that dive deep into your understanding of RAG/memory systems and RLHF/fine-tuning. Prepare to explain your thought process and decision-making in these areas, as it shows your depth of knowledge and practical experience.
