Lead Machine Learning Engineer, Recommendation Systems

Launch Potato; Vancouver; Hybrid; CAD 120,000 - 150,000; Full time

Job summary

A leading tech company is seeking a Lead Machine Learning Engineer for Recommendation Systems. This remote-first role focuses on developing the personalization engine that serves real-time recommendations across millions of user journeys. The ideal candidate has over 7 years of experience in building large-scale ML systems and a strong background in ranking algorithms. Competitive compensation is offered with opportunities for career growth.

Qualifications

• 7+ years building and scaling production ML systems with measurable business impact.
• Fluent in ranking algorithms and proficient in generating engagement from data.
• Experience with modern data processing pipelines and experimentation platforms.

Responsibilities

• Drive business growth by optimizing recommendation systems.
• Own modeling, feature engineering, and data pipelines for user personalization.
• Partner with product, engineering, and analytics teams to launch features.

Skills

Large-scale ML system deployment

Ranking algorithms expertise

Python proficiency

SQL knowledge

Distributed computing familiarity

A/B testing experience

Tools

TensorFlow

PyTorch

Spark

SQL data warehouses

Job description

Overview

Lead Machine Learning Engineer, Recommendation Systems at Launch Potato. Our mission is to connect consumers with the world’s leading brands through data-driven content and technology. We are a remote-first team with a presence in South Florida and 15+ countries, emphasizing speed, ownership, and measurable impact.

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, serving 100M+ predictions daily to impact 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!

We are an Equal Employment Opportunity employer. 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, veteran status, disability, or other legally protected characteristics.