Lead LLM Engineer in Gloucester

Lead LLM Engineer in Gloucester

Gloucester 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 an 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.

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 Gloucester 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 Gloucester

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’s make it shine!

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 who knows, they might even refer you directly to the hiring team!

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 LLM systems and how you’ve tackled similar problems in the past.

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 that extra step to engage with us directly.

We think you need these skills to ace Lead LLM Engineer in Gloucester

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 applying, 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 in your application. We’re looking for someone who enjoys ownership and autonomy, so don’t be afraid to share what makes you tick and why you’re passionate about AI.

Tailor Your LinkedIn Profile:Since you can apply with your LinkedIn profile, ensure it’s up-to-date and reflects your most relevant experiences. We want to see your journey and how it aligns with the role of AI Tech Lead.

Apply Through Our Website:We encourage you to apply directly through our website. It’s the easiest way for us to keep track of your application and get back to you quickly. Plus, we love seeing candidates take that extra step!

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.