Senior Machine Learning Engineer, Recommendation Systems
Launch Potato is a profitable digital media company with monthly visitors over 30M+ through brands like FinanceBuzz, All About Cookies, and OnlyInYourState.
As a launch and conversion company, our mission is to connect consumers with the world’s leading brands through data‑driven content and technology.
Headquartered in South Florida with a remote‑first team spanning 15+ countries, we’ve built a high‑growth, high‑performance culture where speed, ownership, and measurable impact drive success.
Why Join Us
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.
Required Experience
- 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 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
EEO Statement
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.
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