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 for a quick start.
- Why this job: Join a dynamic team solving complex AI challenges and make a real impact.
- Qualifications: Strong Python/PyTorch experience and knowledge of 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 Leicester 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 Leicester
✨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 opportunities, and who knows, they might even refer you directly!
✨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 Leicester
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 you've engaged with AI technologies and what excites you about the field. Share any projects or experiences that highlight your love for building innovative systems.
Tailor Your Application:Make sure to customise your application to fit the Lead LLM Engineer role. Highlight your experience with Python, PyTorch, and any relevant production-scale ML/LLM systems. We appreciate when candidates take the time to align their skills with what we're looking for!
Be Authentic:We value authenticity, so don’t be afraid to let your personality come through in your application. Share your journey, your challenges, and what makes you unique. This helps us get a sense of who you are beyond just your technical skills.
Apply Through Our Website:Remember, the best way to apply is through our website! It’s super easy and ensures your application gets to the right place. Plus, it shows us that you’re keen on joining our team at StudySmarter!
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 dig deep into your understanding of RAG/memory systems and RLHF/fine-tuning. Prepare to explain your thought process and decision-making in past projects, as this will show your depth of knowledge and practical experience.
