Lead Machine Learning Engineer, Recommendation Systems

Launch Potato; Curitiba; Híbrido; BRL 150.000 - 200.000; Tempo integral

Resumo da oferta

A leading technology company is seeking a Lead Machine Learning Engineer to build a personalization engine for its portfolio of brands. You will design and optimize ML systems to deliver real-time recommendations for millions of users. The role requires extensive experience in ML systems, ranking algorithms, and strong programming skills in Python with frameworks like TensorFlow or PyTorch. The company promotes a diverse and inclusive culture, offering opportunities for growth in a remote-first environment.

Qualificações

• 7+ years of experience in building large-scale ML systems.
• Strong background in ranking algorithms and data-driven engagement.
• Familiarity with distributed computing frameworks.

Responsabilidades

• Build and deploy ML models for 100M+ predictions daily.
• Enhance data processing pipelines for efficiency.
• Design algorithms for relevance and diversity.

Conhecimentos

Building and scaling production ML systems

Ranking algorithms knowledge

Proficiency with Python

SQL skills

Experience with Spark and distributed computing

A/B testing knowledge

Ferramentas

TensorFlow

PyTorch

Snowflake

BigQuery

Redshift

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.

WHY JOIN US?

At Launch Potato, 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 continuous optimization.

We’re hiring a Machine Learning Engineer (Recommendation Systems) to build the personalization engine behind our portfolio of brands. You’ll design, deploy, and scale ML systems that power real-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 revenue 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:

• 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'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.