Lead ML Engineer, Recommendation Systems (BE963)

Lead ML Engineer, Recommendation Systems (BE963)

Overview

Lead ML Engineer, Recommendation Systems at Launch Potato.

You will design, deploy, and scale ML systems that power real-time recommendations across millions of user journeys and directly impact engagement, retention, and revenue at scale.

Responsibilities

- Drive business growth by building and optimizing the recommendation systems that personalize experiences for millions of users daily
- Own modeling, feature engineering, data pipelines, and experimentation to improve personalization, speed, and impact
- Build and deploy ML models serving 100M+ predictions per day
- Enhance data processing pipelines (e.g., Spark, Beam, Dask) for efficiency and reliability
- 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

Qualifications

- 7+ 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 (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

Competencies

- Technical Mastery: ML architecture, deployment, and tradeoffs
- Experimentation Infrastructure: MLflow, W&B;, rapid testing and retraining
- Impact-Driven: models that move revenue, retention, or engagement
- Collaborative: works with engineers, PMs, and analysts
- Analytical Thinking: analyzes data trends and designs rigorous tests
- Ownership Mentality: post-deployment ownership and continuous improvement
- Execution-Oriented: production-grade systems delivered quickly with rigor
- Curious & Innovative: stays at ML advances and applies them to personalization

We’re committed to 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 legally protected characteristics.

Seniority level: Mid-Senior level | Employment type: Full-time | Job function: Engineering and Information Technology | Industries: Advertising Services

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Required Skill Profession

Tecnología Eléctrica Y Energética

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