Who we are / The Team
Bloomberg's CTO Office is the future-looking technical and product arm of Bloomberg L.P. We envision, design, and prototype the next generation infrastructure, hardware, and applications for the Bloomberg Terminal. Our projects include machine learning-powered products, cloud computing infrastructure and strategy, open source stewardship, natural language processing, and more. We are passionate about what we do.
What We Do
For more than a decade, Bloomberg has been a trailblazer in its application of AI, Machine Learning, and Natural Language Processing (NLP) in finance. We build models and systems that power sentiment analysis, classification, question answering, document understanding, recommendation, and more, using state of the art AI techniques including generative AI.
Critical to this effort are our AI platforms, which enable teams to rapidly and robustly develop, deploy and maintain AI products and features. As a Technical Product Manager, you will share ownership of the product roadmap for our AI platforms, ensure that we are future proof, expand our user base, and build out new features and capabilities to fulfill our mission. You will work in a group of other highly motivated product managers that work on a range of adjacent projects in AI. You will interact very closely with internal stakeholders from product and engineering. This is a high-leverage role in a very cross-functional environment, so you'll need to be comfortable wearing many hats and balancing technical expertise with business acumen.
What's in it for you / Your Role
We are looking for an experienced professional with a technical background to design and deliver infrastructure to support data onboarding, engineering, and cataloging for AI. As a product manager, you will be responsible for platforms that service the unique needs of developers creating AI-driven applications at Bloomberg. Examples of areas you could be working on include:
• Simplifying data enablement workflows; liaising with data-producing teams at Bloomberg to onboard data for AI and make relevant metadata discoverable.
• Streamlining data access patterns throughout the entire machine learning lifecycle, from exploratory data science and analytics, to large-scale training, to feedback pipelines at model serving time.
• Expanding our infrastructure portfolio with data quality, enrichment, and other data value-add needs to make a cohesive experience when curating AI-ready data.
We'll trust you to
• Partner closely with AI product teams to accelerate their critical machine learning projects, with a preliminary focus on data enablement initiatives for generative AI
• Interact with our machine learning and data science experts, interview them to understand their workflows and technical requirements, develop a deep understanding of their data needs
• Develop a roadmap, design patterns and tools needed to empower, operationalize, and automate data delivery
• Foster a culture of collaboration with your Engineering counterparts
• Prioritize, plan, make decisions, ask the right questions, and understand how to manage resources effectively
• Develop a long-term technical strategy, roadmap, framework, guard rails, design patterns, tools for improving data access to support ML workflows
• Do the right thing; be part of a Product team and CTO organization that optimizes for the long term
You'll need to have
• 5 + years of experience in a Product Management role
• Experience working with data teams and automating ML and other data-intensive applications development workflows
• Deep understanding of identity and access management
• Organizational and communication skills to effectively coordinate and work with engineers, other product managers, and senior management
• A product-driven focus and track record of shaping business strategy and roadmaps for technical products
• A degree in Computer Science, Engineering, Data Science, similar field of study or equivalent work experience
We'd love to see
• Experience with public cloud providers such as AWS, GCP, or Azure, or cloud-based machine learning platforms
• Proven data literacy, understanding of data lineage and provenance
• Breadth of knowledge around data streaming, storage, cataloging, and retrieval technologies such as S3, HDFS, Hadoop, HBase, Hive, Trino, Presto, Cassandra, Spark, Flink, Kafka
• Prior experience as a technical product manager or engineering technical lead
• Open source involvement or community presence
Learn more about us
We are very active in technical communities, both internally and externally. Read more about us:
• The journey to build Bloomberg's ML Inference Platform Using KServe (formerly KFServing)
• Bloomberg's Open Source company values
• Artificial Intelligence (AI) | Bloomberg L.P. | About, Careers, Products, Contacts
• Bloomberg awarded first CNCF End User Award for its contributions to Kubernetes and more | Cloud Native Computing Foundation
