Sr. Software Engineer – Machine Learning Infrastructure


Who We Are
Cyngn is a Silicon Valley-based autonomous vehicle startup backed by leading Venture Capital firms, including Andreessen Horowitz, Benchmark Capital, and Index Ventures.

We are a team of engineers and scientists, and we believe in building the best products through open and honest collaboration. We’re constantly experimenting, asking questions, listening to feedback, and taking action.

The journey of creating and building is just as important as the final product. We pride ourselves on our trusting and creative work environment; it’s what has led us to build one of the world’s leading autonomous vehicle solutions. Our advanced self-driving system is cost-effective, modular, and broadly applicable across a variety of industries and vehicles by leveraging applied artificial intelligence, leading-edge sensors, and robotics. 

Who We’re Looking For
To build this incredible technology, we are looking for energetic, motivated, and experienced technical leaders to help guide our team and move this innovative field forward.

We want you to bring a passion for autonomous vehicles and the future of mobility with a zen-like ability to excel in a fast-paced startup environment. You are driven, curious, calm , and thrive on opportunities to make a big impact on technologies that will revolutionize entire industries while creating commercial success for Cyngn and its partners. 

If you love to build, tinker, and create with a team of trusted colleagues, then Cyngn is the place for you.

About This Role
At Cyngn we strive to build a flexible autonomy stack that can support a variety of vehicles operating in various operating environments. In order to achieve this, we are building a highly efficient data acquisition pipeline, reliable machine learning model development infrastructure, and many more tool kits to support both rapid prototyping and production deployment of high quality ML models.




  • Develop and maintain a data pipeline to efficiently and reliably collect, process, annotate, augment, and manage datasets for ML model training.
  • Develop and maintain frameworks and toolkits to support model evaluation, model version management, model CI/CD, model debugging, model deployment, etc. 
  • Design architecture of ML infrastructure systems to ensure high reliability, efficiency, and maintainability. Making decisions on key tradeoffs between performance and system attributes when necessary.
  • Collaborate with ML experts to understand technical requirements for different stages of model development life cycle.



  • BS/MS in computer science, robotics, similar technical field of study, or equivalent practical experience.
  • 3+ years experience writing C++ and/or Python software in a production environment – unit testing, code review, algorithm performance trade-offs, etc.
  • Experience architecting and developing large-scale, data intensive, production quality backend systems.
  • Strong written & verbal communication skills.

    Bonus Qualifications


  • Proficiency with libraries such as Tensorflow, Pytorch, Numpy, SciPy, OpenCV (Python), etc.
  • Hands-on experience building ML data pipelines, MLOps, model evaluation, model CI/CD, large scale data visualization, etc. 
  • Hands-on experience with computer vision and/or machine learning projects.
  • Hands on experience in image processing and/or point cloud processing.