Form a deep understanding of our Machine Learning Engineers’ needs and our current capabilities and gaps.
Mentor our talented junior engineers on how to build high quality software, and take their skills to the next level.
Continually raise our engineering standards to maintain high-availability and low-latency for our 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.
What we look for in you (ie. job requirements):
5+ yrs of industry experience as a Software Engineer.
You have a strong understanding of distributed systems.
You lead by example through high quality code and excellent communication skills.
You have a great sense of design, and can bring clarity to complex technical requirements.
You treat other engineers as a customer, and have an obsessive focus on delivering them a seamless experience.
You have a mastery of the fundamentals, such that you can quickly jump between many varied technologies and still operate at a high level.
Nice to Have:
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).
