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Senior Applied AI Engineer - Artificial Intelligence

  • Toronto, ON, Canada

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Job details

Posting language
English
Posted

Original job description

Senior Applied AI Engineer - Artificial Intelligence

Description & Requirements

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.

Join the AI Department as a Senior Applied AI Engineer and you will have the opportunity to:


  • Collaborate with colleagues on production systems and write, test, and maintain production quality code

  • Design, train, experiment, and evaluate ML models, agentic systems, algorithms and solutions

  • Demonstrate technical leadership by owning cross-team projects

  • Stay current with the latest research in ML/AI and incorporate new findings into our models and methodologies

  • Represent Bloomberg at scientific and industry conference and in open-source communities

  • Publish product and research findings in documentation, whitepapers or publications to leading academic venues


We are looking for Senior Applied AI Engineers with the following experience:


  • Ph.D. in Computer Science, AI/ML, NLP or relevant technical field with 0–2 years of experience, or a Master’s with 4+ years, or a Bachelor’s with 5+ years of relevant industry experience. 

  • Practical experience applying machine learning, deep learning, and generative AI techniques to real-world problems, from experimentation through production deployment.

  • Strong software engineering skills, including proficiency in Python and experience designing, testing, and maintaining scalable production systems.

  • Hands-on experience building LLM-powered applications, including retrieval-augmented generation, prompt engineering, model evaluation, or post-training techniques.

  • Experience developing agentic AI systems that use external tools, APIs, search systems, databases, or code execution environments.

  • Experience building agentic harnesses or orchestration frameworks, including tool routing, state and memory management, multi-step workflows, guardrails, tracing, retries, and evaluation.

  • Strong computer science fundamentals, communication skills, and the ability to collaborate across technical and non-technical teams; publications at leading AI, ML, or NLP conferences are a plus.

If this sounds like you: 

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.

For some positions, we use automated assessment technologies to assist in selecting appropriate candidates based on criteria we have identified. These automated decisions are made by applying criteria that have been rigorously set by Bloomberg using human input and judgment, and may include communication, decision-making, innovation or teamwork.

Discover what makes Bloomberg unique - watch our podcast series for an inside look at our culture, values, and the people behind our success.

Location

Toronto

Business Area

Engineering and CTO

Ref #

10053563

More about this job

Responsibilities

You will design, train, and evaluate machine learning models and agentic systems while collaborating on production-quality code. Additionally, you will provide technical leadership for cross-team projects and stay current with the latest AI research to drive model refinement.

Requirements

Candidates must hold a Ph.D. with up to 2 years of experience, a Master's with 4+ years, or a Bachelor's with 5+ years of relevant industry experience. Strong proficiency in Python and practical experience deploying generative AI and machine learning solutions to production are required.

Skills

  • Machine Learning
  • Artificial Intelligence
  • Python
  • Large Language Models
  • Retrieval-Augmented Generation
  • Prompt Engineering
  • Agentic Systems
  • Deep Learning
  • Natural Language Processing
  • Software Engineering
  • Model Evaluation
  • Reinforcement Learning
  • Gradient Boosted Decision Trees
  • Vector Databases
  • Code Generation
  • Distributed Systems

Visa sponsorship

Not detected in the job text

Categories

  • Technology
  • Software
  • Data & Analytics
  • Engineering
  • Finance & Accounting

Keywords

  • Machine Learning
  • Artificial Intelligence
  • Python
  • Transformers
  • Large Language Models
  • Retrieval-Augmented Generation
  • Prompt Engineering
  • Agentic Systems
  • Deep Learning
  • Natural Language Processing
  • Gradient Boosted Decision Trees
  • Vector Databases
  • Reinforcement Learning
  • SFT
  • RLHF
  • CoT
  • Software Engineering
  • Financial Technology
  • Data Analytics
  • Model Evaluation
  • Production Deployment
  • Algorithms
  • API
  • Code Execution
  • Orchestration Frameworks
  • State Management
  • Memory Management
  • Guardrails
  • Tracing
  • Whitepapers

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