Jobs · Engineering · California

Embedded Software Engineer, Drive-By-Wire

Gatik · Santa Clara, CA · 1 mo ago
On-siteEngineering$160k–$260k/yrFull-time

About the role

We are seeking a passionate Embedded Software Engineer to join our Drive-By-Wire team to build and improve chassis control software for integration onto common ECU hardware. You will play a critical part in building robust and functionally safe control solutions for Level 4 autonomous technology.

What you'll do

  • Create and improve vehicle chassis controls software for integration on common ECU hardware for vehicle controls.
  • Create functionally safe software by following common automotive standards for functional safety.
  • Design and propose toolchains for seamless integration of model-based application software on ECU firmware.
  • Collaborate with requirements engineers to align the maturity of software and requirements for successful validation.
  • Create and track software release plans as well as testing activities to achieve continuous integration of software products in vehicle and field testing.
  • Bring-up for autonomous vehicle build, including troubleshooting, software testing, and verification.
  • Develop and implement test plans for routine software releases and changes, including both on-vehicle and simulation testing.
  • Evaluate the performance of different AV components, such as sensors, actuators, and algorithms, to ensure they meet safety and performance requirements.
  • Investigate and debug issues found during testing, working with other engineers to resolve problems and improve system performance.
  • Collaborate with other engineers, including software, hardware, and systems engineers, to ensure seamless integration and performance of AV systems.
  • Integrate software and hardware components, ensuring proper functionality and performance within the overall vehicle system.
  • Participate in tuning, calibration, triaging, in-vehicle testing, visualization, and post-processing of test data.

What we're looking for

  • M.S. or Ph.D. in automotive engineering, computer engineering, electronics/electrical engineering, or a related field.
  • 2+ years of experience in embedded automotive systems in the field of ADAS/AD or vehicle chassis controls.
  • Experience in developing and implementing full-time critical systems.
  • Experience with standards and practices such as ISO26262, MISRA-C, AUTOSAR, or similar.
  • Experience in creating automated software generation toolchains.
  • Experience with C programming and Simulink-based modeling using MATLAB.
  • Experience with various testing and calibration tools, including Vector CANalyzer, CANape, Kvaser, New Eagle Raptor CAL, V-box, and ETAS INCA.
  • Experience with vehicle CAN network and configurations, J1939, CAN FD, and automotive Ethernet.
  • Bonus Points: Experience in steering and brake controls, familiarity with dSPACE and vehicle dynamic modeling toolchains, familiarity with SiL/HiL setup and automotive-grade simulation tools such as TruckMaker, hands-on experience with vehicle and aero dynamics, powertrain systems, suspension/compliance, steering/braking systems, and tire modeling.

Salary Range

$160,000- $260,000

More about Gatik

Founded in 2017 by experts in autonomous vehicle technology, Gatik has rapidly expanded its presence to Mountain View, Dallas-Fort Worth, Arkansas, and Toronto. As the first and only company to achieve fully driverless middle-mile commercial deliveries, Gatik holds a unique and defensible position in the AV industry, with a clear trajectory toward sustainable growth and profitability. We have delivered complete, proprietary AV technology - an integration of software and hardware - to enable earlier successes for our clients in constrained Level 4 autonomy. By choosing the middle mile – with defined point-to-point delivery, we have simplified some of the more complex AV challenges, enabling us to achieve full autonomy ahead of competitors. Given extensive knowledge of Gatik’s well-defined, fixed route ODDs and hybrid architecture, we are able to hyper-optimize our models with exponentially less data, establish gate-keeping mechanisms to maintain explainability, and ensure continued safety of the system for unmanned operations.

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