Bloomberg Law, Tax & Government (BLAW/BTAX/BGOV) delivers AI-powered solutions that integrate trusted editorial content with billions of documents and data points to support legal, tax, accounting, and government professionals.

The Product AI Enablement Team builds ML and AI solutions to solve concrete business problems, embedding them directly into user workflows and iterating rapidly using early customer feedback.

What you’ll work on

An example of a current project involves building agentic AI workflows for corporate tax compliance. Agents will analyze complex tax spreadsheets, identify relevant tax topics, retrieve recent statutory and regulatory changes from Bloomberg datasets, generate grounded analysis with citations, and guide users through impacted calculations using a conversational interface. Agents then suggest changes to spreadsheet cells by reasoning over tables, formulas, dependencies, layout, and user-specific spreadsheet styling.

Technical focus

We apply a wide range of ML and NLP techniques, including:

• Agentic AI: tool-calling, MCP configuration, context engineering, prompt tuning, deep research, agent routing, conversational frameworks

• Information Enrichment: NER/disambiguation, classification, topic modeling

• Content Generation: summarization, document drafting, legal insight generation, recommendation systems

We leverage internal platforms for Information Retrieval, Agent Factory, Conversational AI, Knowledge Graphs, Reasoning Models, and Guardrails to deliver end-to-end solutions.

How we work

You’ll work in a forward-deployed, agile environment with software engineers, product managers, subject matter experts, and annotators. We prioritize iterative development, early customer engagement, and rapid feedback-driven improvement. ML ambiguity is expected; success requires ownership, adaptability, and strong collaboration.

Responsibilities

• Lead ML projects end-to-end as the primary technical owner

• Translate business problems into well-scoped ML problems

• Design and develop domain-specific ML, NLP, and LLM-based solutions

• Define evaluation metrics and make data-driven decisions

• Write and maintain production-quality ML code

• Collaborate with AI platform, data, and frontend engineers for deployment and lifecycle management

• Manage stakeholder expectations throughout development and release

• Stay current with ML/NLP research and apply relevant advances

Requirements

• 4+ years of experience in ML/AI, preferably NLP

• Proven experience delivering production NLP systems

• Strong intuition for problem formulation and model selection

• Proven delivery of production NLP systems and integration in user workflows

• Experience with GenAI evaluations, grounding, AI safety & compliance

• MS or PhD in Computer Science, Mathematics, or equivalent practical experience

Nice to have

• Familiarity with weak supervision, reinforcement learning, semantic search, and knowledge graphs

• Systems thinking for Agentic design & tool-using for multi-step agentic workflows

• Experience across the full ML lifecycle: scoping, data collection, training, evaluation, optimization, and deployment

• Research publications, ML competitions, or demonstrable projects

• Interest in legal, tax, or government domains (prior experience not required)