Autonomous Driving

AUTONOMOUS DRIVING

I have led cloud infrastructure management across AWS, and private clouds, utilizing Terraform for Infrastructure as Code (IaC) and DevOps practices to build scalable, resilient systems. This includes optimizing compute, storage, networking, and security for big data workloads, ensuring high availability and compliance in regulated automotive settings.

Autonomous Driving Toolchain Development

I led the deployment of the cloud-based toolchain for data-driven autonomous vehicle development on AWS Kubernetes clusters, integrating with S3 and private cloud storage for secure, privacy-compliant storage of converted vehicle data (ROS format). This platform manages multi-modal sensor data from LiDAR, cameras, and radar through end-to-end workflows, including collection, anonymization, processing, ML model training, ADAS function analysis, and planning & control algorithm simulation, while supporting efficient scenario extraction (RAG-based) and edge case prioritization to accelerate algorithm improvements. I ensured traceability, data quality governance, and adherence to automotive standards like E-NCAP. The secure pipelines enables rapid iteration on safety-critical features—optimized for cost-efficiency based on GPU utilization.

🎤 TechAD Europe 2025 Speaker
Presented groundbreaking work on autonomous driving toolchain development at TechAD Europe 2025 in Berlin

SaaS Platform Migration & Fleet Management

I led the migration of a SaaS platform for real-time consumer fleet data collection from Alibaba Cloud to AWS, re-architecting Kubernetes-based Java microservices with Nacos for service discovery. It features IoT Core with MQTT5 for telemetry ingestion, bidirectional communication with 2-way mTLS auth, Lambda for decoding, S3 for storage, and Glue/Redshift for analytics, processing streams like periodic signals, EDR uploads for AEB/SRS events, and syslog data. I implemented ingestion pipelines for hourly vehicle data cross-cloud synchronization, secure S3 uploads via temporary STS credentials and AKSK tokens, and real-time streaming through MSK (Kafka) and Kinesis Firehose for data analysis service.

AWS Booth, IAA 2023, Munich

TechAD Europe 2025, Berlin

ADAS Expo 2025, Stuttgart

Experience

Senior Algorithm Engineer	2022 – Current	Lotus Tech	+
Architected and manage a cloud-native SaaS platform on AWS supporting ADAS data processing and data-closed loops for autonomous automotive systems. Oversaw compliance, data lifecycle, infrastructure reliability, and performance optimization for ADAS workloads across hybrid cloud architectures. Built Kubernetes-based data platforms that process 10M+ daily sensor data points using MSK, Lambda, S3, and Redshift, implementing automated ML workflows for ADAS model training. Drive business development initiatives with external automotive clients—gathering requirements, shaping technical proposals, and delivering POCs to win projects and expand partnerships.
Senior Algorithm Engineer	2019 –2022	Aptiv	+
Led radar processing algorithms for Motional's Robotaxi, enhancing sensor fusion libraries with Python, C++, and in-house cloud-based toolchains. Led POC development of lane change prediction and ADAS features for BMW and Stellantis clients. Delivered error-handling APIs with ROS, ensuring ASPICE-compliant solutions.
Software Engineer	2016 – 2019	Groupon	+
Built REST APIs in Java and Scala, enabling 6M+ daily customer notifications and GDPR compliance for EMEA. Migrated Hive to Spark, boosting performance 10x and cutting data pipeline runtime by 50%+. Designed and implemented scalable data processing architectures using Apache Spark, Kafka, and cloud-based data warehouses for real-time analytics and customer insights.
Robotics Engineer Intern	2015 – 2015	Auro Robotics	+
As Motion Planning Engineer at Auro Robotics during YC Summer 2015, I developed ROS-based path planning algorithms for a driverless campus shuttle from scratch. Worked directly with co-founders in Mountain View garage, integrating GPS and LiDAR for autonomous navigation. Successfully demonstrated at Stanford campus during YC Demo Day, securing $2.1M funding from Sam Altman and investors.

Yang Song, Ph.D.