Software Engineer – Collision Avoidance System Metrics

Jobtailor; California (MO); On-site; USD 120,000 - 180,000; Full time

Job summary

Jobtailor seeks a research engineer to apply distributed computing to analyze petabytes of urban driving data and to develop metrics and tools for system performance improvements. You will collaborate with CAS, Perception, Planning, and QA teams to validate features and measure performance in complex urban environments.

The role requires a BS/MS/PhD in CS, fluency in C++ and/or Python, and strong experience in programming and algorithm design.

Qualifications

• BS, MS, or PhD degree in computer science or a related field.
• Fluency in C++ and/or Python.
• Extensive experience with programming and algorithm design.
• Experience with analysis of latency for safety-critical software systems (bonus qualification).
• Experience with petabyte-scale distributed computing, including Spark, Databricks, or generic MapReduce pipelines (bonus qualification).
• Background in Bayesian statistics (bonus qualification).

Responsibilities

• Apply distributed computing algorithms to analyze petabytes of urban driving data.
• Develop metrics and tools to analyze errors and system improvements.
• Work closely with CAS engineers to evaluate system performance.
• Collaborate with Perception engineers to define metrics for autonomous driving.
• Partner with Planning engineers to measure performance in complex urban environments.
• Define and build metrics to measure Collision Avoidance System performance.
• Work with Systems Design and Mission Assurance and QA teams to develop validation plans for features.

Skills

C++ Programming

Python Programming

Distributed Computing

Algorithm Design

Performance Analysis

Education

BS/MS/PhD in Computer Science or related field

Tools

Spark

Databricks

MapReduce

Job description

• Apply distributed computing algorithms to analyze petabytes of urban driving data
• Develop metrics and tools to analyze errors and system improvements
• Work closely with CAS engineers to evaluate system performance
• Collaborate with Perception engineers to define metrics for autonomous driving
• Partner with Planning engineers to measure performance in complex urban environments
• Define and build metrics to measure Collision Avoidance System performance
• Work with Systems Design and Mission Assurance and QA teams to develop validation plans for features

Requirements

• BS, MS, or PhD degree in computer science or a related field
• Fluency in C++ and/or Python
• Extensive experience with programming and algorithm design
• Experience with analysis of latency for safety-critical software systems (bonus qualification)
• Experience with petabyte-scale distributed computing, including Spark, Databricks, or generic MapReduce pipelines (bonus qualification)
• Background in Bayesian statistics (bonus qualification)

Core Competencies

Demonstrates expertise in distributed computing algorithms and performance analysis for safety-critical software systems, with a strong foundation in programming and algorithm design. Proficient in developing metrics and tools for evaluating system performance in complex urban environments.

Highest-signal resume keywords

• C++ Programming
• Python Programming
• Distributed Computing
• Algorithm Design
• Performance Analysis

Hard Skills

• Programming
• Algorithm Design
• Metrics Development
• Error Analysis
• System Improvement

Industry Keywords

• Petabyte-Scale Data
• Collision Avoidance System
• Bayesian Statistics
• Safety-Critical Software

Tools & Technologies

• Spark
• Databricks
• MapReduce