As the Founding AI Engineer at Presential Limited, you will own the entire model layer, fine-tuning and distilling small language models (SLMs) to match frontier performance while ensuring data privacy. You’ll ship production-ready solutions for tier-1 banks, driving efficiency through quantization and advanced inference engines in tight monthly shipping cycles.
Founding AI Engineer / Researcher at Presential Limited
Join Presential Limited as a Founding AI Engineer and lead the development of the privacy layer for enterprise AI. You'll own the model layer, fine-tuning small language models that allow tier-1 banks to process sensitive data securely with external AI tools. This is a rare pre-seed opportunity to define a new category, shipping high-performance, production-ready models on one-month cycles. If you're a senior ML researcher with a track record of shipping and a desire to lead, your work here will define the future of secure enterprise intelligence.
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Location
Remote
Compensation
Not Disclosed
Company
Presential Limited
Role overview
What? Presential is building the privacy layer for AI.
Why? Every organisation with sensitive data is stuck between a technology that works and a rulebook that says no. That gap is our market and it widens with every model release.
How? Using our RSP technology, sensitive data goes in, fictional substitutes that carry the same meaning come out, the model runs on those, and we reverse the mapping so the answer arrives whole. The model never sees the real thing. Never.
Who? A small team that has already built successful companies and lived this problem first hand.
Where? London based and already working with enterprise scale customers.
What you will do
- Fine-tune, distill, and domain-adapt SLMs like Llama and Mistral for pseudonymisation and context-preserving text transformation tasks.
- Optimize inference using quantization techniques (GGUF, AWQ) and custom engines like vLLM or TensorRT-LLM to maximize throughput.
- Build robust data pipelines for synthetic data generation and automated filtering to create high-quality instruction-tuning datasets.
Who this is a fit for
- 5+ years of hands-on experience in Machine Learning and NLP, specifically focusing on LLM/SLM development and deployment.
- Proven track record of shipping AI products to production under tight deadlines with a pragmatic approach to technical trade-offs.
- Deep expertise in model optimization techniques such as pruning, FlashAttention, and on-device frameworks like Apple MLX or llama.cpp.
Why this role is remarkable
- Own the core technical bet: making small models match frontier performance on sensitive bank data at production-level latency.
- Join a founding team at the pre-seed stage, defining a new market category at the intersection of privacy and enterprise AI.
- Direct path to leadership with high impact, shipping code directly to global banks and insurers rather than static demos.
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