Senior Language Modeling Engineer - Bloomberg Law/Tax/Gov
Bloomberg
Bloomberg Law/Tax/Gov delivers AI-powered tools that integrate premium editorial content, billions of documents and data points into workflows of legal, tax, accounting and government professionals. Our goal is to become an indispensable tool for legal, tax, accounting and government professionals by supporting their day-to-day tasks and providing solutions that help them get real-time answers and better serve their clients and needs.
We are looking for Senior Machine Learning Engineers with strong expertise in NLP and extensive experience with Large Language Model research & passion for generative AI applications to join our team. Our team researches state of the art LLM techniques with the goal of enabling development of industry leading applications, which help our clients get accurate answers to their complex natural language questions, and assist them in their workflow on our platform.
Key focus areas include: Adapting LLMs to legal, government and tax domains through pretraining and fine-tuning, novel data preparation techniques, efficient training methodologies, LLM alignment from feedback and human preferences, automatic evaluation of generative AI, LLM benchmarking, trustworthy AI, retrieval-augmented generation, question answering and text summarization.
Key focus areas include: Adapting LLMs to legal, government and tax domains through pretraining and fine-tuning, novel data preparation techniques, efficient training methodologies, LLM alignment from feedback and human preferences, automatic evaluation of generative AI, LLM benchmarking, trustworthy AI, retrieval-augmented generation, question answering and text summarization.
What's in it for you:
Collaborate with colleagues from product development and core AI development teams to understand business needs and map them to LLM techniques to solve their needs
Prepare high quality and representative data sets.
Train, tune, evaluate and continuously improve LLMs using large amounts of high-quality data to develop state-of-the-art NLP models for the Law, Government and Tax domains
Collaborate with colleagues from our platform team to train and deploy the LLMs
Write, test, and maintain production quality code
Demonstrate technical leadership by owning cross-team projects
Stay current with the latest research in AI, NLP and LLMs and incorporate new findings into our models and methodologies and benchmark them
Publish product and research findings in documentation, whitepapers or publications to leading academic venues
Collaborate with colleagues from product development and core AI development teams to understand business needs and map them to LLM techniques to solve their needs
Prepare high quality and representative data sets.
Train, tune, evaluate and continuously improve LLMs using large amounts of high-quality data to develop state-of-the-art NLP models for the Law, Government and Tax domains
Collaborate with colleagues from our platform team to train and deploy the LLMs
Write, test, and maintain production quality code
Demonstrate technical leadership by owning cross-team projects
Stay current with the latest research in AI, NLP and LLMs and incorporate new findings into our models and methodologies and benchmark them
Publish product and research findings in documentation, whitepapers or publications to leading academic venues
You'll need to have:
Practical and subject matter experience in Natural Language Processing
A Ph.D. in ML, NLP or a relevant field or MSc in CS, ML, Math, Statistics, Engineering, or related fields and 2+ years of relevant work experience
5+ years of experience in Python and Machine Learning (ML) toolkits and platforms such as PyTorch, Hugging Face, JAX or scikit-learn.
Experience with Generative AI, training & inference of Large Language Models.
We’ll love to see:
An understanding of Computer Science fundamentals such as data structures and algorithms and a data oriented approach to problem-solving
Experience with cloud platforms for ML Model training and deployment
Excellent communication skills and the ability to collaborate with engineering peers as well as non-engineering stakeholders.
A track record of authoring publications in top conferences and journals
Experience in law, tax or government affairs.
Practical and subject matter experience in Natural Language Processing
A Ph.D. in ML, NLP or a relevant field or MSc in CS, ML, Math, Statistics, Engineering, or related fields and 2+ years of relevant work experience
5+ years of experience in Python and Machine Learning (ML) toolkits and platforms such as PyTorch, Hugging Face, JAX or scikit-learn.
Experience with Generative AI, training & inference of Large Language Models.
An understanding of Computer Science fundamentals such as data structures and algorithms and a data oriented approach to problem-solving
Experience with cloud platforms for ML Model training and deployment
Excellent communication skills and the ability to collaborate with engineering peers as well as non-engineering stakeholders.
A track record of authoring publications in top conferences and journals
Experience in law, tax or government affairs.