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David Yang

About

Detail

Santa Clara, California, United States

Timeline


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Résumé


Jobs verified_user 0% verified
  • Aurora
    Staff Software Engineer
    Aurora
    Mar 2025 - Current (1 year 8 months)
    • Designed and implemented scalable Python-based microservices deployed on GCP leveraging Docker and Kubernetes to
    support renewable energy optimization workflows, integrating real-time telemetry data with intelligent decision pipelines while
    ensuring high availability and seamless interoperability with enterprise systems.
    • Developed advanced LLMs-powered applications utilizing RAG pipelines and vector search backed by BigQuery and Redis,
    enabling contextual retrieval of operational energy data and improving decision support systems through efficient embedding-
    based semantic indexing and retrieval.
    • Engineered agentic Al workflows using LangGraph and AutoGen to orchestrate multi-step reasoning tasks across d
  • Cruise
    Senior Applied Scientist II / Senior Software Engineer
    Cruise
    Aug 2020 - Mar 2025 (4 years 8 months)
    • Developed large-scale backend systems using Java and Python within microservices architecture on AWS, supporting data-
    intensive applications in autonomous mobility platforms with emphasis on scalability, fault tolerance, and efficient API
    communication.
    • Built distributed data pipelines leveraging PostgreSQL, Redis, and streaming systems to process real-time vehicle telemetry,
    enabling robust data ingestion and transformation workflows supporting machine learning and analytics use cases.
    • Implemented containerized services using Docker and orchestrated deployments via Kubernetes, improving operational
    consistency and enabling scalable service management across complex distributed environments.
    • Desig
  • Zoox
    Software Engineer
    Zoox
    Jul 2019 - Jul 2020 (1 year 1 month)
    • Developed backend services using C++ and Python to support autonomous vehicle systems, focusing on data processing
    pipelines and efficient communication between distributed modules handling sensor data.
    • Implemented data storage and retrieval mechanisms using SQL and PostgreSQL, enabling structured access to large-scale
    datasets required for machine learning model training and validation workflows.
    • Worked with containerized environments using Docker to ensure consistent development and deployment processes across
    engineering teams working on autonomous mobility systems.
    • Supported integration of machine learning components built with TensorFlow and PyTorch into backend systems, enabling
    real-time inf
  • Byton
    Autonomous Driving Software Engineer
    Byton
    May 2018 - Jul 2019 (1 year 3 months)
    • Developed software components in C++ and Python supporting intelligent vehicle systems, focusing on real-time data
    processing and integration of sensor inputs for autonomous driving features.
    • Worked on backend systems utilizing SQL databases to manage structured data used in model training and validation
    processes for intelligent vehicle platforms.
    • Integrated machine learning models built with TensorFlow into application workflows, enabling predictive capabilities within
    connected vehicle systems.
    • Collaborated on system-level integration ensuring reliable communication between embedded systems and backend
    infrastructure supporting vehicle intelligence.
  • S
    Machine Learning Engineer
    Spark Al
    Aug 2017 - Oct 2017 (3 months)
    • Developed machine learning models using Python and TensorFlow for marketing analytics applications, focusing on predictive
    modeling and customer segmentation use cases.
    • Built data processing pipelines using SQL and ETL workflows to prepare structured datasets for training and evaluation of
    machine learning models.
    • Implemented backend services to expose model predictions through APIs, enabling integration with external tools and
    applications used by marketing teams.
    • Optimized model performance and data workflows, improving efficiency of training and inference processes within resource-
    constrained environments.
Education verified_user 0% verified
  • University of Michigan
    M.S, Industrial and Operations Engineering
    University of Michigan
    Jan 2017 - Jan 2018 (1 year 1 month)
  • University of Michigan
    M.S, Aerospace Engineering
    University of Michigan
    Jan 2016 - Jan 2018 (2 years 1 month)
  • University of Michigan
    B.S.E, Aerospace Engineering
    University of Michigan
    Jan 2014 - Jan 2016 (2 years 1 month)