Applied Machine Learning Engineer - Media Search And Recommendation

at Bloomberg
📍 New York City, United States
USD 165,000-260,000 per year
SENIOR
✅ On-site

Used Tools & Technologies

Not specified

Required Skills & Competences

Python @ 6 Spark @ 4 Java @ 6 Algorithms @ 3 Distributed Systems @ 4 Machine Learning @ 6 Data Science @ 4 Leadership @ 4 AWS @ 4 Mathematics @ 4 Performance Monitoring @ 4 Data Analysis @ 4 API @ 4 Experimentation @ 4 .NET @ 4 Data Pipelines @ 4

Details

Bloomberg Media empowers global business leaders with breaking news, expert opinion and proprietary data distributed with global reach. With millions of unique visitors each month, bloomberg.com is a top destination for those looking to stay ahead of the curve. The Search and Personalization team owns core discovery experiences on Bloomberg.com and the Bloomberg mobile app, focusing on search, discovery, personalization and recommendations at web scale. Our systems operate at the intersection of backend services, data pipelines, and user-facing experiences.

Responsibilities

  • Lead the design and delivery of personalization and recommendation systems that power discovery across Bloomberg.com and mobile platforms.
  • Build and maintain data pipelines that support personalization, experimentation, and model-driven product experiences.
  • Design, develop, and evolve backend services and APIs that deliver personalized content at scale with low latency.
  • Partner closely with the data science team to productionize models and enable rapid experimentation.
  • Collaborate across the stack, including with frontend engineers, to deliver cohesive and high-quality user experiences.
  • Make architectural decisions, drive technical discussions, and help set technical direction for the personalization platform.
  • Mentor other engineers and raise the overall technical bar of the team.

Requirements

  • 5+ years of industry experience in an Object Oriented Programming language (preferably Python or Java).
  • 5+ years of industry experience working with large data sets, performing machine learning model experimentation, implementation and deployment.
  • A Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent professional experience.

Preferred / Additional Qualifications

  • Exposure building and developing a content recommendation system; familiarity with recommendation algorithms and ML capabilities.
  • Familiarity building user behavioral models to predict user likelihood for high-value actions (e.g., propensity to subscribe or churn).
  • Experience with end-to-end ML projects: data analysis, feature engineering, model selection, hyper-parameter tuning, model deployment and ongoing performance monitoring.
  • Hands-on expertise with big data systems and distributed data processing technologies such as Spark.
  • Proven track record building and maintaining data pipelines that power customer-facing product features.
  • Demonstrated leadership delivering machine learning projects from inception through delivery.
  • Practical expertise with public cloud platforms such as AWS.
  • Proven ability to operate and evolve web-scale distributed systems in production.

Compensation and Benefits

  • Salary Range: 165000 - 260000 USD annually + Benefits + Bonus.
  • Benefits 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) with match, life insurance, and various wellness programs. The Company does not provide benefits directly to contingent workers/contractors and interns.

Notes / Links