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Machine Learning Engineering Team Lead
2 months ago
Bloomberg's Engineering AI department is seeking a highly skilled senior leader to lead our Information Retrieval research team. As a key member of our team, you will be responsible for developing and implementing innovative solutions to complex AI-driven customer-facing products.
Key Responsibilities:- Collaborate with product owners, domain experts, data engineers, and front-end engineers to build high-quality search systems and integrate AI solutions in our products.
- Develop and maintain high-throughput and low-latency services that encapsulate ML models and pipelines using a modern Model Development Life Cycle.
- Lead globally distributed teams, mentor and coach team members, and influence technology strategy.
- Drive results, challenge and influence team members, peers, and stakeholders.
- Experience in building and maintaining high-throughput and low-latency services, preferably those that encapsulate ML models and pipelines using a modern Model Development Life Cycle.
- Leadership experience: managing, mentoring, and coaching globally distributed teams, as well as influencing technology strategy.
- Ability to effectively communicate and drive results, challenge and influence team members, peers, and stakeholders.
- History of successfully delivering on key initiatives and driving long-term strategic technology plans.
- Practical experience with Information Retrieval problems and a familiarity with Machine Learning, LLMs, Deep Learning, or Statistical Modeling techniques.
- Experience with retrieval frameworks and platforms such as Vespa, Apache Solr, or Elasticsearch.
- Experience working with annotators and effectively managing quality of services, models, software, and datasets, including migration to modern technologies such as deep neural networks, especially transformer architectures, including large language models and dense vector databases.
Bloomberg is an equal opportunity employer and values diversity at our company. We do not discriminate on the basis of age, ancestry, color, gender identity or expression, genetic predisposition or carrier status, marital status, national or ethnic origin, race, religion or belief, sex, sexual orientation, sexual and other reproductive health decisions, parental or caring status, physical or mental disability, pregnancy or maternity/parental leave, protected veteran status, status as a victim of domestic violence, or any other classification protected by applicable law.
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