Technical Strategist for AI Research – CTO Office

Details

Bloomberg’s CTO Office is the future-looking technical and product arm of Bloomberg L.P. It designs and prototypes next-generation infrastructure, platforms, and applications for the Bloomberg Terminal, including machine learning-powered products, cloud computing infrastructure and strategy, open source stewardship, and generative AI.

This role is part of the ML Strategy team and focuses on contributing to Bloomberg’s AI research agenda, collaborating with academic and industry partners, engaging with the machine learning community, and shaping Bloomberg’s approach to emerging AI and machine learning developments. A major focus is strengthening the systems and processes that support high-quality, rigorous, reproducible, and externally visible AI research.

Responsibilities

• Contribute to Bloomberg’s research agenda through original research, academic and industry collaboration, and engagement with the broader machine learning research community.
• Strengthen the processes, norms, and infrastructure supporting rigorous, reproducible, and externally visible research.
• Track advances in machine learning and assess their relevance to Bloomberg’s products, platforms, research agenda, and clients.
• Represent Bloomberg’s AI research and technical perspective at conferences, workshops, academic collaborations, and partner engagements.
• Design, streamline, automate, and operate workflows for reviewing, preparing, publishing, and externally communicating AI research.
• Collaborate with researchers, research leadership, Communications, Legal, product, engineering, and external partners.

Requirements

• PhD in AI, machine learning, computer science, statistics, optimization, data science, or a related technical field.
• At least 5 years of post-PhD experience in industry, academia, or a research-oriented organization.
• Strong publication record and credible presence in the AI research community.
• Experience with rigorous research review and publication processes, including peer-reviewed submissions, reproducibility practices, or internal review systems.
• Strong judgment regarding AI research quality, rigor, reproducibility, and responsible external communication.
• Ability to build trust and work effectively across research, product, engineering, communications, legal, and external partner communities.
• Excellent written and verbal communication skills, including the ability to explain technical research context to non-specialist stakeholders.
• Strong organizational skills and an interest in improving complex workflows, systems, and processes.
• Comfort working in ambiguous environments where processes, responsibilities, and edge cases may need to be clarified or improved.

Preferred Qualifications

• Strong publication record in top machine learning venues such as ICLR, ICML, NeurIPS, AISTATS, UAI, KDD, JMLR, or TMLR.
• Active participation in the research community through workshop or tutorial organization, conference service, peer review, academic-industry collaborations, or open research infrastructure.
• Experience designing, improving, or scaling systems that raise the quality, rigor, reproducibility, fairness, efficiency, or impact of research.
• Research expertise in areas including model adaptation, compression and distillation; inference and serving for large models; long-context and memory-augmented systems; reinforcement learning and learning from feedback; synthetic data and data curation; or modern time-series modeling.
• Understanding of financial markets, instruments, and products.
• Exposure to Bloomberg Terminal and/or enterprise data products.

Benefits

Benefits may include merit increases, incentive compensation for exempt roles, paid holidays, paid time off, medical, dental and vision coverage, short- and long-term disability benefits, 401(k) matching, life insurance, and wellness programs.