Junior Forward-Deployed AI Engineer (LLM/ML)
About The Position
At Silent Eight, we develop our own AI-based products to combat financial crimes that enable things like money laundering, the financing of terrorism, and systemic corruption. We’re a leading RegTech firm working with large international financial institutions such as Standard Chartered Bank and HSBC. Join us and help make the world a safer place! We solve hard, real‑world problems — from uncovering financial crime, fraud patterns and mule networks, through prioritising thousands of alerts, to crafting defendable case narratives. We work close to users (analysts, investigators, risk/compliance), iterate fast, and deliver in weeks, not quarters. The adversary adapts — this is an intelligence game, not an academic benchmark. The Role We’re looking for someone who solves business problems with technology. Less stack worship, more outcomes: fast risk identification, fewer false positives, faster time‑to‑decision, better explainability, and lower cost per case. Finance shows up often, but we think broader — investigations, decisions and client value across industries.
Requirements
- Problem‑solving & communication: you can break down fuzzy problems and explain risks to non‑technical stakeholders.
- LLMs + ML in practice: RAG, prompting, tool‑calling; classification/ranking/deduplication; fundamentals of evaluation & experimentation.
- Python + SQL sufficient to build a prototype that works and can be maintained.
- Polish & English fluency for user conversations and concise write‑ups.
Nice To Haves
- A track record of delivery: 2–3 examples where your AI/ML solution materially improved process KPIs (any industry).
- Experience with investigations / trust & safety / fraud / risk / audit or other complex decision processes.
- Graphs/ER: entity resolution, link analysis, pattern‑of‑life.
- Light engineering craft: FastAPI, Docker; the rest (K8s/CI/CD/Terraform) is not required.
Responsibilities
- Go to the field: talk to users, shadow their workflows, capture the as‑is → goals & constraints.
- Define hypotheses & KPIs (precision/recall, FPR, TAT, coverage, cost/decision) and turn them into experiment plans.
- Design decision flows that mix LLMs, retrieval/RAG, classical ML, and lightweight rules; ensure explainability and auditability.
- Build quick prototypes (notebook → lightweight service/API) and measure their impact on real data.
- Create evaluation sets and scoring rubrics (offline + side‑by‑side + sanity checks + guardrails).
- Present findings & recommendations directly to decision‑makers; propose rollout (pilot → production‑lite → scale).
- Lead innovation processes across the company; test, promote solutions and mentor others with new AI technologies.
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What This Job Offers
Job Type
Full-time
Career Level
Entry Level
Education Level
No Education Listed
Number of Employees
101-250 employees
