We are looking for a
Software Algorithm Engineer to design, implement, and maintain robust algorithmic systems in production environments. This role focuses on
high-quality software engineering combined with algorithmic thinking, working on real-world data at scale.
The position requires end-to-end ownership — from problem definition and algorithm design to
production-grade software, deployment, and long-term maintenance.
The main task is to contribute to the software infrastructure that enables autonomous driving, from perception to planning.
Responsibilities:
Software Engineering
- Design modular architectures that separate algorithms, data, and infrastructure
- Build reusable components, libraries, and internal tools
- Perform code reviews and enforce engineering best practices
- Process large-scale datasets (high-resolution images, video, sensor metadata, geospatial data )
- Optimize runtime, memory usage, and I/O performance
Algorithmic Systems Development
- Design and implement algorithmic pipelines (from DL models to classic signal processing algorithms) integrated into production software.
- Translate algorithmic ideas into reliable, scalable, and maintainable code.
- Evaluate algorithm performances using quantitative metrics and visualization tools.
- Ensure reproducibility across development, testing, and different production environments
Collaboration & Ownership
- Work closely with other engineers, researchers, and product teams
- Take full ownership of components throughout their lifecycle
- Contribute to technical design discussions and architectural decisions
Requirements:
- Strong software engineering skills with Python
- Academic degree in one of the following: CS, DS ,SW / Electrical Eng, or similar.
- Experience building production-quality systems, with code versioning and releases.
- Solid algorithmic thinking and data analysis skills.
- Experience working with large datasets and complex data pipelines.
- Strong debugging, profiling, and performance optimization skills.
- Ability to work independently and make technical tradeoffs.
- Familiarity with testing frameworks, CI, and deployment workflows.
Preferred / Nice To Have
- Experience with computer vision or ML systems in production.
- Experience with cloud infrastructure, batch systems, or containerization.
- Experience in autonomous driving, robotics, or real-time systems.
- Experience with Simulation environments.