Software Algorithm Engineer

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
  
  

• 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
  
  

• 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
  
  

• 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.
  
  

• 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.