Senior ML Engineer, Recommendation Systems

Senior ML Engineer, Recommendation Systems Launch Potato Join to apply for the Senior ML Engineer, Recommendation Systems role at Launch Potato. Overview Launch Potato is a profitable digital media company that reaches over 30M+ monthly visitors through brands such as FinanceBuzz, All About Cookies, and OnlyInYourState. As The Discovery and Conversion Company, our mission is to connect consumers with the worlds leading brands through data-driven content and technology. Headquartered in South Florida with a remote-first team spanning over 15 countries, weve built a high-growth, high-performance culture where speed, ownership, and measurable impact drive success. Were hiring a Machine Learning Engineer (Recommendation Systems) to build the personalization engine behind our portfolio of brands. Youll 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. Base salary : $130,000$220,000 per year, paid semi-monthly Why join us At Launch Potato, youll 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. 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 make personalization smarter, faster, and more impactful. 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: ML tooling for rapid testing and retraining (MLflow, W&B). Impact-Driven: Models that move revenue, retention, or engagement. Collaborative: Works well with engineers, PMs, and analysts. Analytical Thinking: Designs rigorous test methodologies from data trends. Ownership Mentality: Post-deployment ownership and continuous improvement. Execution-Oriented: Deliver production-grade systems quickly and rigorously. Curious & Innovative: Applies ML advances to personalization. Employment type : Full-time Job function : Engineering and Information Technology Industries : Advertising Services About our equal opportunities Launch Potato is an Equal Employment Opportunity company. We value diversity, equity, and inclusion. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, gender identity or expression, age, protected veteran status, disability, or other legally protected characteristics. #J-18808-Ljbffr