Senior ML Engineer, Recommendation Systems

WHO ARE WELaunch 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. WHY JOIN USAt 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. 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. MUST HAVEYouve shipped large-scale ML systems into production that power personalization at scale. Youre fluent in ranking algorithms and know how to turn data into engagement and conversions. Specifically : 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 YOUR ROLEDrive business growth by building and optimizing the recommendation systems that personalize experience for millions of users daily. Youll own the modeling feature engineering data pipelines and experimentation that make personalization smarter faster and more impactful. OUTCOMESBuild 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 COMPETENCIESTechnical 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 nowEqual Employment OpportunitySince day one weve 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