Senior ML Engineer, Recommendation Systems
Job Description
Launch Potato, a thriving digital media company reaching over 30M+ monthly visitors, is seeking a Senior ML Engineer specializing in Recommendation Systems. As The Discovery and Conversion Company, we're on a mission to connect consumers with leading brands through data-driven content and technology.
The role offers an exciting opportunity to build and optimize the recommendation systems that power personalization for millions of users across our portfolio of brands. You'll be responsible for designing, deploying, and scaling ML systems that serve 100M+ predictions daily, directly impacting engagement, retention, and revenue at scale.
Working in a remote-first environment spanning 15+ countries, you'll join a high-performance culture where speed, ownership, and measurable impact drive success. The position requires 5+ years of experience building production ML systems, strong expertise in ranking algorithms, and proficiency with Python, SQL, and modern ML frameworks.
Key responsibilities include building real-time personalization systems, enhancing data processing pipelines, designing sophisticated ranking algorithms, and running rigorous A/B tests to measure business impact. You'll collaborate closely with product, engineering, and analytics teams to launch high-impact personalization features while maintaining system reliability and performance.
The compensation package includes a competitive base salary range of $130,000–$220,000, profit-sharing bonus, and comprehensive benefits. This is an excellent opportunity for a seasoned ML engineer looking to make a significant impact by building personalization systems at scale while working with a global team of high-performers.
Responsibilities For Senior ML Engineer, Recommendation Systems
- 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
Requirements For Senior ML Engineer, Recommendation Systems
- 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
Benefits For Senior ML Engineer, Recommendation Systems
- Profit-sharing bonus
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