Senior Machine Learning Engineer, Recommendation Systems

Launch Potato; Delray Beach (FL); On-site; USD 165,000 - 215,000; Full time

Job summary

A digital media company based in Delray Beach, FL is seeking a Senior Machine Learning Engineer to lead the development of recommendation systems that personalize user experiences. This role requires building ML models that serve over 100M predictions daily, with a strong emphasis on ranking algorithms and data processing efficiencies. Ideal candidates have a solid background in ML systems and a passion for driving business impact through technology.

Benefits

Profit-sharing bonus

Competitive benefits

Career growth opportunities

Qualifications

• 5+ years of experience building production ML systems.
• Experience deploying ML systems for high traffic (100M+ predictions).
• Strong knowledge of ranking algorithms and collaborative filtering.

Responsibilities

• Build and optimize recommendation systems for user personalization.
• Design and deploy ML models for real-time predictions.
• Enhance data processing pipelines for efficiency.

Skills

Production ML systems

Ranking algorithms

Python

SQL

Distributed computing

A/B testing

Tools

TensorFlow

PyTorch

Spark

BigQuery

Snowflake

MLflow

Job description

Senior Machine Learning Engineer, Recommendation Systems

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 world’s leading brands through data‑driven content and technology.

Headquartered in South Florida with a remote‑first team spanning over 15 countries, we’ve built 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.

Compensation

$165,000 – $215,000 per year, paid semi‑monthly.

MUST HAVE

• 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

Total Compensation

Base salary is set according to market rates for the nearest major metro and varies based on Launch Potato’s Levels Framework. Your compensation package includes a base salary, profit‑sharing bonus, and competitive benefits. Future increases will be based on company and personal performance, not annual cost‑of‑living adjustments.

Diversity, Equity, Inclusion

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 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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Seniority level

Mid‑Senior level

Employment type

Full‑time

Job function

Engineering and Information Technology

Industries

Advertising Services

Location

Delray Beach, FL