Coinbase is looking to build the foundational components for feature engineering and training/serving ML models at scale to combat fraud, personalize user experiences, and analyze blockchains.
Requirements
- You have a strong understanding of distributed systems.
- You’ve designed, built, scaled and maintained production services.
- Experience building ML models and working with ML systems.
- Experience working on a platform team, and building developer tooling.
- Experience with the technologies we use (Python, Golang, Ray, Tecton, Spark, Airflow, Databricks, Snowflake, and DynamoDB).
Responsibilities
- Advance our high-availability and low-latency ML inference infrastructure that runs both predictive ML models and LLMs.
- Optimize low latency streaming pipelines to give our ML models the freshest and highest quality data.
- Evangelize state-of-the-art practices on building high-performance distributed training jobs that process large volumes of data.
- Build tooling to observe the quality of data going into our models and to detect degradations impacting model performance.
- Form a deep understanding of our Machine Learning Engineers’ needs and our current capabilities and gaps.
Other
- In-person participation is required throughout the year.
- Team and company-wide offsites are held multiple times annually to foster collaboration, connection, and alignment.
- Attendance is expected and fully supported.
- You write high quality code and have excellent communication skills.
- You treat other engineers as a customer, and have an obsessive focus on delivering them a seamless experience.
