Bloomberg

Description & Requirements

Bloomberg Law, Tax & Government (BLAW/BTAX/BGOV) delivers AI-powered solutions that integrate trusted editorial content and billions of documents and data points into the workflows of legal, tax, accounting, and government professionals. Our mission is to be an indispensable resource, empowering our users to make faster, smarter decisions and better serve their clients and constituents.

The Information Enrichment & Content Generation (IECG) Team builds scalable ML solutions for two key areas:

• Information Enrichment: Traditional NLP use-cases such as Named Entity Recognition/Disambiguation, classification, topical modeling etc.
• Content Generation: Generative use-cases such as Summarization, Drafting new documents, Generating legal insights, on-point recommendation systems etc.

We are currently focused on developing advanced research and drafting tools designed to speed up those tasks for our customers by letting AI do the heavy-lifting. These tools let users upload a document, then automatically classify it, structure its contents and analyze the text by identifying topics, extracting entities and suggesting highly relevant references. Some of the specific problems we are working on this year include extracting pragmatics & judicial reasoning of legal cases, drafting legal contracts, analyzing the congressional budget along with government’s actual spending and generating insights to support tax positions.

To solve these, we apply a range of ML/NLP techniques including statistical models, deep neural networks, language models & third-party generative LLMs. We work closely with product managers, software engineers and domain experts in an agile environment.

In general, Machine Learning projects have an intrinsic dose of uncertainty, so a good fit for our team is a person who is self-driven, proactive, comfortable dealing with uncertainty and ambiguity in task definition. We’re a highly collaborative team, both internally and across other teams, so being a teammate and an effective communicator are important for success in our team.

What’s in it for you:

As part of our team, you will be developing machine learning (ML) models to address our business needs. You will drive, design and develop machine learning solutions. The right combination of cross-field ML techniques, deep understanding of the business problem and high-quality training data is fundamental to our models producing high quality models for our clients’ needs. You will collaborate with product managers and domain experts to understand business problems and translate those into appropriate ML problems. You will research groundbreaking ML/NLP techniques and apply them to our business problems. You will collaborate with domain experts to gain valuable insights and use their expertise to get high quality annotated training data. You will work closely with data engineers and front-end engineers to integrate your ML solutions into our products. You will also have the opportunity to work directly with academia, leading research centers as well as to publish your work at conferences.

Legal NLP is an exciting and rapidly evolving field. If you are interested in working with a highly collaborative team to develop innovative solutions and make a big impact, please apply!

We’ll trust you to:

• Drive, design & develop ML projects as the principal point-of-contact
• Collaborate with domain experts and product managers to understand business needs and map business problems to ML Problems
• Learn groundbreaking research in advanced ML & NLP topics and design ML/AI solutions for the problems
• Develop tailored ML/AI prediction models for our domain
• Use metrics to make data-driven decisions
• Write and maintain production-quality code
• Collaborate with AI platform engineers on model maintenance and rollout
• Manage stakeholders’ expectations throughout the project on model development and release

You'll need to have:

• 4+ years of experience in Python
• Proven delivery of production NLP systems
• Intuition to formulate an ML problem from a business problem
• Master’s or PhD in Computer Science, Engineering, Mathematics, similar field of study or equivalent work experience

We’d love to see:

• Knowledge of advanced concepts such as weakly supervised learning, reinforcement learning, semantic search, knowledge-graph construction
• Authored research publications, participation in ML competitions, working demos/repos
• Experience with distributed computational frameworks (Spark, Hadoop, Kubernetes, Databricks)
• Curiosity to learn more about the legal, tax or government domain (prior experience is not required)
• Familiarity with traditional statistical methods, modern deep learning frameworks, prompting LLMs, RAG, vector search
• Experience in all phases of machine learning application lifecycles from problem mapping and scoping to data gathering and preparation to optimizing model performance

Salary Range = 165000 - 260000 USD Annually + Benefits + Bonus

The referenced salary range is based on the Company's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level.

We offer one of the most comprehensive and generous benefits plans available and offer a range of total rewards that may include merit increases, incentive compensation (exempt roles only), paid holidays, paid time off, medical, dental, vision, short and long term disability benefits, 401(k) +match, life insurance, and various wellness programs, among others. The Company does not provide benefits directly to contingent workers/contractors and interns.