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Senior MLOps Engineer
3 months ago
Posted May 23, Requisition No
Bloomberg's Engineering AI department has 300+ 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.
We are looking for Senior MLOps Engineers with strong expertise and passion for building and maintaining AI systems to join our team.
As a Senior MLOps Engineer you will design and build tools to improve the efficiency of our Model Development Life Cycle (MDLC), automate ML processes, enhance the performance of our systems and more.
- Architect, build, and diagnose production AI applications and systems
- Collaborate with colleagues on production systems and write, test, and maintain production quality code
- Define and provide strong SLAs around latency, throughput and resource (memory / disk / network / CPU / GPU) usage
- Work closely with AI Platform teams to operationalize continuous model training, inference, and monitoring workflows
- Proven experience working with an object-oriented programming language (Python, Go, etc.)
- A Degree in Computer Science, Engineering, Mathematics, similar field of study or equivalent work experience
- An understanding of Computer Science fundamentals such as data structures and algorithms
- An honest approach to problem-solving, and ability to collaborate with peers, stakeholders and management
- Industry experience with machine learning teams
- Working knowledge of common ML frameworks such as PyTorch, ONNX, DeepSpeed etc.
- Prior experience with cloud-native technologies like Kubernetes, Argo Workflows, Buildpacks, etc.
- Experience with cloud providers such as AWS, GCP or Azure
- A track record of collaboration with colleagues to achieve repeatable high quality outcomes
Bloomberg is an equal opportunity employer and we value 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.
Bloomberg provides reasonable adjustment/accommodation to qualified individuals with disabilities. Please tell us if you require a reasonable adjustment/accommodation to apply for a job or to perform your job. Examples of reasonable adjustment/accommodation include but are not limited to making a change to the application process or work procedures, providing documents in an alternate format, using a sign language interpreter, or using specialized equipment. If you would prefer to discuss this confidentially, please email (Americas), (Europe, the Middle East and Africa), or (Asia-Pacific), based on the region you are submitting an application for.
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