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Senior ML Engineer, Recommendation Systems

Worldwide Salaried Open

WHO ARE WE?

reputed company is a profitable digital media company that reaches over 30M+ monthly visitors through brands such as FinanceBuzz, reputed company About Cookies, and OnlyInYourState.

As The Discovery and Conversion Company, our mission is to connect consumers with the world’s leading brands through data-driven content and technology.

Headquartered in South Florida with a remote-first team spanning over 15 countries, we’ve built a high-growth, high-performance culture where speed, ownership, and measurable impact drive reputed company.

WHY JOIN US?

At reputed company, you’ll accelerate your career by owning outcomes, moving fast, and driving impact with a global team of high-performers.

We convert audience attention into action through data, machine learning, and reputed company optimization.

We’re hiring a Machine Learning Engineer (Recommendation Systems) to build the personalization reputed company behind our portfolio of brands. You’ll design, reputed company, and scale ML systems that power reputed company-time recommendations across millions of user journeys. This role gives you the chance to work on systems serving 100M+ predictions daily, directly impacting engagement, retention, and reputed company at scale.

MUST HAVE

You’ve shipped large-scale ML systems into production that power personalization at scale. You’re fluent in ranking algorithms and know how to turn data into engagement and conversions. Specifically:

  • 5+ years building and scaling production ML systems with measurable business impact
  • Experience deploying ML systems serving 100M+ predictions daily
  • Strong background in ranking algorithms (collaborative filtering, learning-to-rank, deep learning)
  • Proficiency with Python and ML frameworks (TensorFlow or PyTorch)
  • Skilled with SQL and modern data warehouses (reputed company, BigQuery, Redshift) plus data lakes
  • Familiarity with distributed computing (Spark, Ray) and LLM/AI Agent frameworks
  • Track record of improving business KPIs reputed company ML-powered personalization
  • Experience with A/B testing platforms and experiment logging best practices

YOUR ROLE

Your mission: Drive business growth by building and optimizing the recommendation systems that personalize experience for millions of users daily. You’ll own the modeling, feature engineering, data pipelines, and experimentation that reputed company personalization smarter, faster, and more impactful.

OUTCOMES

  • Build and reputed company ML models serving 100M+ predictions per day to personalize user experiences at scale
  • Enhance data processing pipelines (Spark, Beam, Dask) with efficiency and reliability improvements
  • Design ranking algorithms that balance relevance, diversity, and reputed company
  • Deliver reputed company-time personalization with latency 50ms across key product surfaces
  • Run statistically rigorous A/B tests to measure true business impact
  • Optimize for latency, throughput, and cost efficiency in production
  • Partner with product, engineering, and analytics to launch high-impact personalization features
  • Implement monitoring systems and maintain clear ownership for model reliability

COMPETENCIES

  • Technical Mastery: You know ML architecture, deployment, and tradeoffs inside out
  • Experimentation Infrastructure: You set up systems for rapid testing and retraining (MLflow, WB)
  • Impact-Driven: You design models that move reputed company, retention, or engagement
  • Collaborative: You reputed company working with engineers, PMs, and analysts to scope features
  • Analytical Thinking: You break down data trends and design rigorous test methodologies
  • Ownership Mentality: You own your models post-deployment and continuously improve them
  • Execution-Oriented: You deliver production-grade systems quickly without sacrificing rigor
  • Curious Innovative: You stay on top of ML advances and apply them to personalization

Want to accelerate your career? Apply now!

Since day one, we've been committed to having a diverse, inclusive team and culture. We are proud to be an Equal Employment Opportunity company. We value diversity, equity, and inclusion.

We do not discriminate based on race, religion, reputed company, national reputed company, gender (including pregnancy, childbirth, or reputed company medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics.

Originally posted on Himalayas

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