Lead Machine Learning Engineer, Recommendation Systems

Launch Potato; Quebec; Hybrid; CAD 100,000 - 145,000; Full time

Job summary

A cutting-edge technology company in Canada is seeking a Lead Machine Learning Engineer specializing in recommendation systems. You will drive personalization for millions of users by designing, deploying, and scaling ML systems. The ideal candidate has over 7 years of experience in the field with a strong background in developing impactful ML solutions. This role offers a dynamic, remote-first work environment and ample opportunities for career growth.

Qualifications

• 7+ years building and scaling production ML systems.
• Strong background in ranking algorithms.
• Proficiency with Python and ML frameworks.

Responsibilities

• Drive business growth by building and optimizing recommendation systems.
• Own modeling, feature engineering, data pipelines, and experimentation.
• Deliver real-time personalization with low latency.

Skills

Building and scaling production ML systems

Ranking algorithms knowledge

Proficiency in Python

SQL and modern data warehouses

Distributed computing familiarity

Experience with A/B testing platforms

Tools

TensorFlow

PyTorch

Spark

MLflow

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 headquartered in South Florida with a remote-first team spanning over 15 countries, built on 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, serving 100M+ predictions daily and directly impacting engagement, retention, and revenue at scale.

Must Have

• 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 experiences 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 company. We value diversity, equity, and inclusion, and 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, protected veteran status, disability, or other legally protected characteristics.