1:00 PM - 2:00 PM
Senior Product Manager Interview
Sarah Jenkins
Location
onsite, Toronto, ON, Canada
Commitment
Full Time
Level
Senior (5+ years)
Bloomberg’s Engineering AI department has 450+ AI practitioners building highly sought after products and features that often require novel innovations. We are investing in AI to build better search, discovery, and workflow solutions using technologies such as transformers, gradient boosted decision trees, large language models, and dense vector databases. We are expanding our group and seeking highly skilled individuals who will be responsible for contributing to the team (or teams) of Machine Learning (ML) and Software Engineers that are bringing innovative solutions to AI-driven customer-facing products.
At Bloomberg, we believe in fostering a transparent and efficient financial marketplace. Our business is built on technology that makes news, research, financial data, and analytics on over 35 million financial instruments searchable, discoverable, and actionable across the global capital markets.
Bloomberg has been building Artificial Intelligence applications that offer solutions to these problems with high accuracy and low latency since 2009. We build AI systems to help process and organize the ever-increasing volume of structured and unstructured information needed to make informed decisions. Our use of AI uncovers signals, helps us produce analytics about financial instruments in all asset classes, and delivers clarity when our clients need it most.
In Toronto, our Applied AI Engineers are central to Bloomberg's work on financial query understanding, code generation and agentic systems over structured data. They bridge the gap between pioneering research and production, building models and agents that answer complex financial questions, write and execute code, and bring new datasets into the platforms our clients query every day. They engineer state-of-the-art code generation and agent systems, build the evaluation loops that tell us whether those systems are right, and apply LLM techniques like CoT, SFT or RLHF to drive iterative model refinement.
Apply if you think we're a good match! We'll get in touch with you to let you know what the next steps are. In the meantime, check us out at http://www.techatbloomberg.com/ai
This posting is for an open position at Bloomberg.
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