Forward‑Deployed AI Engineer
1 tydzień temu
- Python
- SQL
- FastAPI
Take ownership of deploying, integrating, and maintaining company products in client environments.
Use technology to solve business-critical problems.
Focus on improving risk detection, fewer false positives, faster decisions, better explanations, and lower cost per case.
Your responsibilities- Engaging directly with users - observing their workflows, understanding current processes, constraints, and desired improvements.
- Defining measurable hypotheses and KPIs such as precision/recall, false-positive reduction, turnaround time, coverage, and cost efficiency.
- Designing decision pipelines combining LLMs, retrieval systems/RAG, classic ML components, and lightweight rules - all with auditability and explainability in mind.
- Prototyping fast - from notebooks to small APIs/services - and validating results on real datasets.
- Preparing evaluation datasets and scoring rubrics including offline tests, side-by-side comparisons, sanity checks, and guardrails.
- Presenting outcomes to business leaders and proposing rollout strategies (pilot → production-lite → full deployment).
- Driving internal innovation, sharing findings, mentoring peers, and promoting effective AI practices across the company.
- Proven delivery track record 2–3 concrete cases where your AI/ML work significantly improved key metrics in any domain.
- Strong analytical and communication skills - ability to clarify ambiguous problems and explain risk/impact to non-technical audiences.
- Hands-on experience with LLMs and ML - RAG pipelines, prompt design, tool-calling, ranking/classification/dedup tasks, and sound evaluation techniques.
- Practical Python and SQL skills sufficient to build maintainable prototypes.
- Fluency in English and Polish for user interviews and concise documentation.
- Background in risk, fraud, investigations, audit, or trust & safety settings.
- Understanding of graphs/ER, entity matching, link analysis, or behavioral pattern discovery.
- Comfort with light engineering (FastAPI, Docker). No requirement for Kubernetes/Terraform/CI-CD.
- in house
- you have influence on the product
- agile
- backend developer
- data scientist
- project manager
- documentation
- mentoring
- space for experimenting
- substantive support from technological leaders
- Fully remote work
- Influence over decisions
A small, experienced team operating in short feedback loops.
Weekly objectives, rapid iterations, and a build-test-learn culture.
User proximity is central to our process.
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