Design and ship productionized ML pipelines, from raw data and ETL through model inference and orchestration
Build and deploy ML-powered APIs and services that support real user-facing features
Own the full lifecycle of ML systems: experimentation, deployment, monitoring, and iteration
Develop ML systems for personalization, search, and recommendations
Work with embedding-based systems and vector representations (text, images, or multimodal data)
Measure results rigorously and iterate based on real-world performance
Create and maintain data pipelines and internal tooling
Deploy and operate ML systems in production (AWS, containerization, EC2, service orchestration)
Ensure systems are scalable, reliable, and observable
Monitor model and system performance and improve robustness over time
Maintain a high standard for code quality, testing, and system design
Collaborate closely with leadership and peers to shape technical direction
Move quickly while balancing correctness, reliability, and long-term maintainability

Bachelor or PhD in Data Science, Artificial Intelligence, Computer Science or Machine Learning
4+ years experience building or contributing to ML systems used in production
Experience with embeddings, retrieval, ranking, or recommendation systems
Ability to ship end-to-end solutions, not just models or analyses
Strong programming skills (Python required)
String data querying and manipulation skills (Pandas, SQL)
Comfort working across data, modeling, APIs, and infrastructure
Experience operating ML systems at meaningful scale (startup or large company)

Senior Machine Learning Engineer

Key skills