Senior Applied AI Engineer — AI, Code Gen & Agent Systems

Bloomberg; Toronto; On-site; CAD 140,000 - 190,000; Full time

Job summary

Bloomberg’s Engineering AI team in Toronto seeks a Senior Applied AI Engineer to build AI-driven search, discovery, and workflow features. You will work across ML and software engineers to bring innovative AI solutions to customer‑facing products, bridging research and production.

You will design, train, and evaluate ML models and agentic systems, publish findings, and participate in open‑source and academic venues. Strong Python and production‑scale experience are essential.

Qualifications

• Ph.D./Master’s/Bachelor’s with significant AI/ML research or industry experience.
• Hands‑on ML/DL and generative AI techniques applied to real-world problems.
• Strong software engineering skills with Python and scalable systems.
• Experience building LLM-powered apps and retrieval augmented generation.
• Experience with agentic AI systems using tools, APIs, and databases.
• Publications at AI/ML/NLP venues are a plus.

Responsibilities

• Collaborate on production systems, write and maintain production quality code.
• Design, train, experiment, and evaluate ML models and agentic systems.
• Demonstrate technical leadership by owning cross-team projects.
• Stay current with ML/AI research and integrate findings into models.
• Represent Bloomberg at conferences and in open‑source communities.
• Publish product and research findings in documentation or publications.

Skills

Python

ML

NLP

Deep learning

LLM applications

Agentic AI

Software engineering

Education

PhD in Computer Science/AI/NLP

Master’s with 4+ years

Bachelor’s with 5+ years

Job description

Bloomberg’s Engineering AI team in Toronto seeks a Senior Applied AI Engineer to build AI-driven search, discovery, and workflow features. You will work across ML and software engineers to bring innovative AI solutions to customer‑facing products, bridging research and production.

You will design, train, and evaluate ML models and agentic systems, publish findings, and participate in open‑source and academic venues. Strong Python and production‑scale experience are essential.