Senior Machine Learning Engineer, Recommendation Systems

Overview Senior Machine Learning Engineer, Recommendation Systems — part of the Launch Potato team, a profitable digital media company with brands including FinanceBuzz, All About Cookies, and OnlyInYourState. The Discovery and Conversion Company connects consumers with leading brands through data-driven content and technology. Headquartered in South Florida with a remote-first team spanning 15 countries. 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, including systems serving 100M predictions daily to impact engagement, retention, and revenue at scale. Responsibilities 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 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 5 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 for rapid testing and retraining. Impact-Driven: Models that move revenue, retention, or engagement. Collaborative: Works with engineers, PMs, and analysts to scope features. Analytical Thinking: Designs rigorous test methodologies. Ownership Mentality: Post-deployment ownership and continuous improvement. Execution-Oriented: Delivers production-grade systems quickly with rigor. Curious & Innovative: Stays on top of ML advances and applies them to personalization. Equal Opportunity 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. 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. J-18808-Ljbffr

Location: Rio de Janeiro, Rio de Janeiro, BR

Posted Date: 10/25/2025