Lead LLM Engineer in York

Lead LLM Engineer in York

York Full-Time 185000 - 185000 £ / year (est.) Working from home possible
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At a Glance

  • Tasks: Lead AI projects, optimise systems, and write production code in a dynamic environment.
  • Company: Fast-scaling AI business with a global remote team and engineering-led culture.
  • Benefits: Up to £185K base salary, £60K equity, and fully remote work.
  • Other info: Direct access to the CTO and a small, talented AI team.
  • Why this job: Join a pioneering AI company making waves with millions of users and cutting-edge technology.
  • Qualifications: Strong Python/PyTorch experience and a passion for building scalable AI 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 York 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.

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Contact Details:

Tact Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Lead LLM Engineer in York

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 into the company culture and expectations.

Tip Number 3

Prepare for technical interviews by brushing up on inference optimisation and latency at scale. Be ready to discuss your hands-on experience with production-scale ML/LLM systems, as this will be key to impressing the hiring team.

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 York

Python
PyTorch
vLLM
Hugging Face
Production-scale ML/LLM systems
Inference Optimisation
Latency at Scale

Some tips for your application 🫡

Show Off Your Skills:When you're filling out your application, make sure to highlight your experience with Python, PyTorch, and any production-scale ML/LLM systems you've worked on. We want to see how you've tackled engineering challenges in the past!

Be Authentic:Let your personality shine through! We’re looking for someone who enjoys ownership and autonomy, so don’t be afraid to share your passion for AI and what drives you in your work. It’s all about finding the right fit!

Tailor Your LinkedIn Profile:Since you can apply with your LinkedIn profile, make sure it’s up-to-date and reflects your most relevant experiences. Highlight projects where you've shipped AI products used by millions – that’s a big plus for us!

Apply Through Our Website:We encourage you to apply directly through our website. It makes the process smoother for both of us, and we can get back to you quicker. Plus, it shows you’re serious about joining our team!

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 aligns with the company culture.

Cultural Fit Matters

Research the company’s values and culture, especially their engineering-led approach. Be prepared to discuss how your background from startups or Tier 1 companies aligns with their team dynamics and how you can contribute to their rapid growth.