Senior Machine Learning Engineer, Recommendation Systems
Skills
- Proven experience shipping production ML systems that power personalization at scale
- Strong knowledge of ranking algorithms (collaborative filtering, learning-to-rank, deep learning)
- Proficiency in Python and ML frameworks (TensorFlow or PyTorch)
- Advanced SQL skills and experience with modern data warehouses (Snowflake, BigQuery, Redshift)
- Familiarity with distributed compute frameworks (Spark, Ray) and real-time inference
- Experience designing and analyzing A/B tests and experiment logging
Responsibilities
- Design, implement, and deploy recommendation and ranking models for personalization across multiple products
- Build and maintain data pipelines and feature engineering workflows (Spark, Beam, Dask) to support model training and inference
- Operate real-time inference systems with target latencies under 50ms and throughput for 100M+ predictions/day
- Run statistically rigorous A/B tests and analyze experiments to quantify business impact
- Monitor model performance and reliability; own retraining, rollbacks, and production health
- Collaborate with product, engineering, and analytics to prioritize features and align models with business KPIs
- Optimize models and infrastructure for latency, cost, and accuracy
Education
- Bachelor’s degree in Computer Science, Engineering, Statistics, or related field OR equivalent practical experience
- Master’s degree or higher in a quantitative discipline preferred but not required
Benefits
- Base salary range $130,000–$220,000 per year (paid semi-monthly)
- Profit-sharing bonus and performance-driven compensation
- Remote-first team with international colleagues
- Competitive benefits package
- Opportunity for rapid career growth and high-impact ownership
- Inclusive, diverse work culture
Average salary estimate
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