Lucid is looking to solve the problem of accelerating the delivery of Advanced Driver-Assistance Systems (ADAS) features to customers by developing robust, scalable software tools and pipelines. This includes automating the characterization of failures, monitoring real-world performance, triaging issues, and performing root-cause analysis of anomalies using large-scale vehicle data.
Requirements
- 5+ years of software development experience for embedded systems or in an automotive or cloud environment. (3+ years with a Master's degree).
- Strong proficiency in Python or C/C++.
- Hands-on experience with cloud development platforms such as AWS/Azure/OCI.
- Familiarity with machine learning frameworks such as TensorFlow, PyTorch, or JAX.
- Knowledge of vector databases and their application in large-scale data analysis.
- Experience with Generative AI models and fine-tuning (preferred).
Responsibilities
- Design and develop robust, scalable software tools and pipelines that increase the velocity of ADAS feature delivery to customers.
- Architect and implement systems to automatically characterize ADAS feature failures, monitor real-world performance, and triage issues.
- Build and maintain tools to automate the root-cause analysis of ADAS anomalies using large-scale vehicle data.
- Collaborate closely with embedded software, AI, and QA teams to understand their needs and deliver tools that enhance productivity and quality.
- Leverage cloud development tools and data platforms to build high-performance data pipelines for ADAS performance analysis.
- Contribute to the strategic vision for our ADAS toolchain, identifying opportunities to apply advanced techniques like generative AI to improve efficiency.
Other
- BS or MS degree in Computer Science, Computer Engineering, or a related field.
- Excellent problem-solving skills and the ability to work effectively in a fast-paced with remotely distributed teams in a collaborative environment
