Building an open financial system and combating fraud, personalizing user experiences, and analyzing blockchains through machine learning.
Requirements
- Strong understanding of distributed systems.
- Mastery of the fundamentals, such that you can quickly jump between many varied technologies and still operate at a high level.
- Experience building ML models and working with ML systems (nice to have).
- Experience working on a platform team, and building developer tooling (nice to have).
- Experience with technologies such as Python, Golang, Ray, Tecton, Spark, Airflow, Databricks, Snowflake, and DynamoDB (nice to have).
Responsibilities
- Form a deep understanding of Machine Learning Engineers’ needs and current capabilities and gaps.
- Mentor junior engineers on building high-quality software.
- Raise engineering standards to maintain high-availability and low-latency for ML inference infrastructure.
- Optimize low-latency streaming pipelines to give ML models the freshest and highest quality data.
- Evangelize state-of-the-art practices on building high-performance distributed training jobs.
- Build tooling to observe the quality of data going into models and detect degradations impacting model performance.
Other
- 5+ years of industry experience as a Software Engineer.
- Lead by example through high-quality code and excellent communication skills.
- Great sense of design, and can bring clarity to complex technical requirements.
- Treat other engineers as a customer, and have an obsessive focus on delivering them a seamless experience.
- In-person participation is required throughout the year, including team and company-wide offsites.
- Commitment to diversity in the workforce and equal opportunity employment.
