Uddhava Jawalkar

About Uddhava Jawalkar

I am a Hardware Reliability Engineering leader in self-driving technology. With over 8 years of experience in mechatronic systems engineering, I enjoy solving complex problems and integrating multiple systems while maximizing efficiency and performance.My mission is to engineer new products that improve the everyday lives of individuals and are designed to make transportation safer and sustainable for all. I have a proven track record of leading product reliability improvements, implementing game-changing validation processes, developing control requirements and strategies, and collaborating with multidisciplinary teams. My expertise includes Automotive ECU calibration and development, Electric Powertrains, Electric Vehicle Modules, and On-board Diagnostic Tuning. I am passionate about advancing the AV technology with Cruise

Experience

1. Hardware Software Integration Engineer

   Zoox

   Mar 2024 — Present · San Francisco, CA, US

   Lead and drive debugging of hardware-software issues in vehicle systems, ensuring operational stability and product reliability through rigorous testing and issue resolution, leveraging AI-powered diagnostics and ML-driven anomaly detection. Identify root causes of complex system failures by collaborating with cross-functional teams, including hardware, software, manufacturing, and quality assurance, utilizing predictive analytics and machine learning models to detect failure patterns and enhance system resilience. Provide critical design feedback to engineering teams to improve future product versions, incorporating AI-driven insights, sensor fusion techniques, and real-time data processing methodologies. Develop and execute advanced test plans that align with vehicle assembly and regulatory requirements, supporting scalable manufacturing operations with AI-enhanced automation and robotic-assisted testing. Design and implement automated testing solutions, leveraging in-house data analytics, deep learning models for defect detection. Work cross-functionally to characterize vehicle functionality, autonomous features, and real-world performance, integrating AI/ML-based perception models, sensor calibration algorithms, and real-time inference systems to optimize vehicle behavior. Lead integration activities for thermal management systems, ensuring optimal AI hardware health in safety-critical situations by deploying adaptive thermal regulation and real-time cooling optimization. Leverage fleet reliability experience to improve readiness for operational launch, implementing AI-powered predictive maintenance strategies, deep learning models for anomaly detection, and fleet-wide data aggregation for performance insights. Develop and refine processes and human-machine workflows to enhance fleet stability, optimize vehicle lifecycle management, and reduce operational costs, autonomous diagnostic tools.

Education

• North Carolina State University

  Master’s Degree, Mechanical Engineering

• Savitribai Phule Pune University

  Bachelor of Engineering (BE), Mechanical Engineering

Skills

• Minitab
• Microsoft Word
• Matlab
• Microsoft Office
• Geometric Dimensioning & Tolerancing
• Rapid Prototyping
• Mechanical Engineering
• Research
• Finite Element Analysis
• Dfmea
• Autocad
• Dvp&R
• Advanced Product Quality Planning (Apqp)
• New Product Development (Npd)
• Sea - Statistical Energy Analysis
• Six Sigma
• Testing
• Va One
• Design of Experiments
• Manufacturing
• Engineering
• Microsoft Excel
• Powerpoint
• C
• Microsoft Powerpoint
• Catia
• Project Management
• Solidworks
• Customer Service
• Management
• Prototyping
• Ansys
• Cad
• Labview
• Cae - Computer Aided Engineering
• Automotive Engineering
• Ni Labview
• Computer-Aided Design (Cad)
• Product Development
• Dfma