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Senior Software Engineer - ML Ops - Data Technologies

Bloomberg

Bloomberg

Software Engineering, Operations, Data Science
New York, NY, USA
Posted on Friday, February 2, 2024

Senior Software Engineer - ML Ops - Data Technologies

New York, NY

Posted Feb 1, 2024 - Requisition No. 122964

Our team

The Bloomberg Engineering Data Technologies Department engineers systems and models that serve billions of data points to some of the World’s most discerning customers each day.

The Applied Modeling team strives to create and share insights by leveraging our internal partners’ deep domain expertise and applying Machine Learning methods to Bloomberg’s petabytes of data. We're a dynamic, collaborative and intellectually stimulating bunch, working together on interesting problems to bring impact to our customers and clients. We care deeply about building a diverse, inclusive organization, and hope that you can join us in this exciting work!

We're seeking an exceptional Software Engineer (MLOps) to join us. You will lead the charge in applying advanced machine learning models to address intricate financial and investment business challenges.

We’ll trust you to:

  • Rigorously develop & deploy resilient, production ML systems that power new insight and prediction features used by our clients in the finance and investment industries.
  • Collaborate with data scientists, machine learning engineers, financial & investment domain experts, and others to transform prototypes into production grade implementations.
  • Maintain and develop the tooling and lifecycle processes for model development and deployment along with other members of the team. This includes ETL, data engineering, data preprocessing, training, evaluation, deployment, monitoring, and reporting.
  • Engage with open-source communities and internal platforms to curate a cohesive MLOps experience for the team.

You’ll need to have:

  • 4+ years of experience with an object-oriented programming language such as Java or Python
  • 4+ years of experience with common software development lifecycle practices
  • Demonstrated expertise in deploying machine learning models to real-world environments, utilizing technologies such as Docker, Kubernetes, and cloud platforms
  • A degree in Computer Science, Engineering, Mathematics, similar field of study or equivalent work experience

We’d Love to See:

  • Experience using Apache Spark and other distributed data processing technologies
  • Experience deploying both batch and streaming ML services
  • Experience with ML/Statistics frameworks such as PyTorch, PyTorch lightning, Tensorflow, Statsmodels, or pymc
  • Strong understanding of machine learning and statistical modeling concepts and techniques

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 AMER_recruit@bloomberg.net (Americas), EMEA_recruit@bloomberg.net (Europe, the Middle East and Africa), or APAC_recruit@bloomberg.net (Asia-Pacific), based on the region you are submitting an application for.


Salary Range: 160,000 - 240,000 USD Annually + Benefits + Bonus

The referenced salary range is based on the Company's good faith belief at the time of posting. Actual compensation may vary based on factors such as geographic location, work experience, market conditions, education/training and skill level. We offer one of the most comprehensive and generous benefits plans available and offer a range of total rewards that may include merit increases, incentive compensation [Exempt roles only], paid holidays, paid time off, medical, dental, vision, short and long term disability benefits, 401(k) +match, life insurance, and various wellness programs, among others. The Company does not provide benefits directly to contingent workers/contractors and interns.