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Lead Machine Learning Engineer, Recommendation Systems

Launch Potato

Salvador

Híbrido

BRL 636.000 - 850.000

Tempo integral

Hoje
Torna-te num dos primeiros candidatos

Resumo da oferta

A technology-driven company is seeking a Lead Machine Learning Engineer to enhance personalized user experiences through innovative recommendation systems. The ideal candidate has extensive experience in ML system deployment, ranking algorithms, and collaboration with cross-functional teams. This remote-first role offers the chance to significantly impact business growth and user engagement through advanced ML architecture and experimentation.

Qualificações

  • 7+ years building and scaling production ML systems with measurable business impact.
  • Strong background in ranking algorithms (collaborative filtering, learning-to-rank, deep learning).
  • Proficiency with Python and ML frameworks (TensorFlow or PyTorch).

Responsabilidades

  • Drive business growth by building and optimizing recommendation systems.
  • Ensure delivery of real-time personalization with low latency.
  • Run A/B tests to measure business impact.

Conhecimentos

Building and scaling production ML systems
Ranking algorithms
Python programming
SQL proficiency
Distributed computing
A/B testing

Ferramentas

TensorFlow
PyTorch
Snowflake
BigQuery
Redshift
Spark
Descrição da oferta de emprego
Lead Machine Learning Engineer, Recommendation Systems

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 success.

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:

  • 7+ years building and scaling production ML systems with measurable business impact
  • 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 (Snowflake, BigQuery, Redshift) plus data lakes
  • Familiarity with distributed computing (Spark, Ray) and LLM/AI Agent frameworks
  • Track record of improving business KPIs via 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 make personalization smarter, faster, and more impactful.

OUTCOMES
  • Build and deploy 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 revenue
  • Deliver real-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, W&B)
  • Impact-Driven: You design models that move revenue, retention, or engagement
  • Collaborative: You thrive 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 have 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, color, national origin, gender (including pregnancy, childbirth, or related 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.

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