Senior Staff Software Engineer ML Platform

Role overview

• check_circle Data Mining: We are building a framework and infrastructure to find interesting events quickly and flexibly. As part of this mission, you would be setting the direction for and helping us build an inference service using LLMs, open-world models and vector databases.
• check_circle Semantic Search for Data Mining: We are building the infrastructure of a highly scalable semantic search service for multimodal data to find interesting events quickly and flexibly. As part of this mission, you would be setting the direction for and helping us build an inference service using the latest AI models & approaches.
• check_circle Dataset management for training: We are building state of the art infrastructure to support machine learning training and inference workloads using OSS components such as Ray, Spark, Lance and Iceberg.

Responsibilities

• check_circle Build state-of-art multimodal data mining and semantic search solutions to power AV product development.
• check_circle Develop data understanding platform infrastructure for real-time querying/vector databases and batch/stream processing using technologies like Ray, Spark, Lance, or similar.
• check_circle Deliver end-to-end data mining solutions that span onboard (C++) and offboard (ML & Data Infra) infrastructure to accelerate AV product development.
• check_circle Develop e2e solution for real-time semantic search services (text/images/videos) and vector DBs.
• check_circle Discover and identify key issues in existing ML infra and proactively improve system performance.
• check_circle Build low latency/high throughput batch or stream processing pipelines.
• check_circle Drive technical discussions across multiple orgs and deliver solutions on a timely basis.
• check_circle Architect and tune ETL pipelines to maximize GPU/CPU/Ram utilization.
• check_circle Write readable and high-performance Python/C++ code.
• check_circle Experience with both ML platforms and building ML-based applications (modeling experience is a bonus).
• check_circle Proven track record of building scalable, reliable infrastructure in a fast-paced environment.
• check_circle Ability to collaborate effectively across teams.
• check_circle Experience building or using ML infrastructure for a large number of customer teams.
• check_circle Deep understanding of design trade-offs with the ability to articulate those trade-offs and achieve alignment with others.
• check_circle Experience in building ML models or infrastructure in domains such as autonomous vehicles, perception, and decision-making (desirable but not required).
• check_circle Experience with model training, model optimization, or large data processing pipelines.
• check_circle Prior experience in autonomous vehicles (AV) is a plus.
• check_circle 6+ years of experience with: Multimodal data indexing and inference pipelines. Building semantic search service, embedding generation for video/images and vector DB. Large scale ML pipelines (Airflow/Flyte) and model optimization.
• check_circle Multimodal data indexing and inference pipelines.
• check_circle Building semantic search service, embedding generation for video/images and vector DB.
• check_circle Large scale ML pipelines (Airflow/Flyte) and model optimization.

About the company