Staff Applied Scientist (Compliance & Operations)

34k - 47k PLN34 000 - 47 000 PLN/ mies./ mies.B2BB2B (netto)

SeniorHybryda·KrakówFull-time·B2B

#471365·Dodano 5 dni temu·0

Źródło: justjoin.it

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Tech Stack / Keywords

Python SQL PyTorch Machine Learning NLP Large Language Models (LLMs)

Podsumowanie oferty

As a Staff Applied Scientist, you’ll build models and AI workflows that help Bizee understand documents, identify relevant requirements, and complete operational work. You’ll investigate data, train and adapt models, design evaluations, and partner with engineers to bring solutions into production for compliance and operations.

Wymagania

Track record in applied science or machine learning, defining problems under uncertainty and taking models from experimentation into sustained business use.
Strong foundations in statistics, machine learning, and experimental design, with deep expertise in NLP, information retrieval, or document understanding; able to diagnose model failures and design experiments to improve them.
Hands-on experience training and adapting models, including practical work with LLMs; understanding of transformer models, embeddings, retrieval, and fine-tuning.
Strong Python and SQL skills, experience with PyTorch or an equivalent framework, and ability to write tested, maintainable code for reproducible experiments and production collaboration. Use AI tools to accelerate work while verifying generated code and analysis.
Experience with noisy documents, limited labels, and unevenly distributed failure cases; able to assess data quality, build representative evaluation sets, quantify uncertainty, and account for different costs of mistakes.
Sound judgment about AI reliability and sensitive data; able to address unsupported outputs, prompt injection, and data exposure, and design traceable results with appropriate review and fallback behavior.
Autonomy to identify problems when goals or evidence conflict, prioritize experiments, and make practical trade-offs. Communicate clearly in English and establish methods and decisions that help colleagues work independently.
Master’s or PhD in computer science, machine learning, statistics, or a related discipline, or equivalent experience demonstrating comparable scientific depth and delivery.

Nice to have:

Experience with compliance, legal, financial, or document-intensive products, including evaluation with domain experts.
Experience with workflow automation, process analysis, or operational decision systems, including measuring exceptions and manual review.
Experience with parameter-efficient fine-tuning, model distillation, or agentic systems that retrieve information, use tools, and complete tasks with appropriate permissions and review.
Experience operating ML systems in the cloud, or research and open-source contributions demonstrating original thinking and practical impact.

Obowiązki

Partner with Operations, Product, Engineering, and compliance experts to identify opportunities, challenge assumptions, and define hypotheses and success measures.
Develop models and AI workflows for document classification, information extraction, routing, and operational decisions; test their effects on completion time, error rates, manual review, and cost.
Build scientific approaches for identifying business requirements and answering compliance questions, connecting outputs to authoritative sources and defining when the system should abstain or request human review.
Train, fine-tune, and evaluate models; compare traditional machine learning, pretrained models, retrieval-augmented generation, and supervised fine-tuning.
Develop training and evaluation datasets, define labeling guidance, address data gaps and imbalance, and prevent leakage between training and testing. Use synthetic data or active learning where they demonstrably improve quality.
Create repeatable evaluations of retrieval quality, factual accuracy, task completion, and consequential failure cases using Bizee documents and workflows, expert review, and validated automated checks. Set release criteria and rerun evaluations after material changes.
Own scientific outcomes through production and adoption, partnering with engineers to deploy and monitor models, diagnose performance changes, and improve latency and cost. Build feedback loops, track data and model versions, and define when to retrain, revise, or retire a solution.
Track advances in AI and test relevant ideas; explain results and trade-offs, document experiments, and share reusable methods.

Benefity

Stock options.
Annual bonus.
Flexible benefits allowance to spend on what matters to you.

Udziały pracownicze

Premie

Bizee

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