LLM Data Scientist (up to £120k + Equity)
Zettafleet · London, United Kingdom ·
- Employment
- Full time
- Category
- Data science
- Experience
- 1+ years
- Salary
- GBP 75,000 – 120,000 / year
Zettafleet · London, United Kingdom ·
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Zettafleet is hiring a forward-deployed LLM Data Scientist in London (on-site) to embed with enterprise clients, building data pipelines that turn raw data into training-ready Parquet for domain-adapted LLMs and embedding models. Core work spans Python data science, synthetic data generation, and LLM training workflows (CPT, SFT, DPO, RL).
Role: LLM Data Scientist (Forward-Deployed)
Location: London (On-site; Liverpool Street)
Employment Type: Full-time and Permanent
Remuneration: £75k – £120k Base Salary + Discretionary Bonus + Equity
Zettafleet is an end-to-end platform for businesses and organisations to train their own LLM on their proprietary data. We can use non-conventional AI hardware and automatically source and combine GPUs (and other types of AI accelerators) from multiple cloud providers, enabling users to optimise for cost, duration or geographic location of the training.
The founding team consists of Oxford and Cambridge graduates and former engineers at Google, Meta, Microsoft and Amazon. We are backed by prominent investors from the US and the UK, including institutional VC funds and C-level executives of global technology companies.
We are looking for a high-impact Forward-Deployed LLM Data Scientist to bridge the gap between enterprise data environments and advanced AI models. In this high-visibility, customer-facing technical role, you will embed with client teams to turn their raw data into clean Parquet files for training of domain-adapted LLMs and embedding models. You will act as both a data scientist and consultant, advising clients on the complete data lifecycle – from dataset creation and synthetic data generation to identifying the right data retrieval and LLM training strategies.
In this role, you will:
What we are looking for:
We would like to acknowledge that almost no candidate checks every box – and that is perfectly fine. If you are passionate about solving complex challenges and open to learning new technologies, we would love to hear from you.
Nice to have:
How we work:
Why join us?