Lead Software Engineer – Control

About the role

We are seeking a highly skilled software engineer to advance Avride's core Control System. In this role, you will architect sophisticated control systems using Model Predictive Control (MPC) and identify the dynamic parameters of our vehicles.

We are seeking a Lead Software Engineer to drive the technical evolution of Avride's core Control System. This role is roughly 80% hands-on engineering and 20% technical leadership — you'll spend most of your time architecting and shipping Model Predictive Control (MPC) systems and vehicle dynamics models yourself, while also setting technical direction and unblocking a small team of 2-3 control engineers.

What you'll do

Hands-on (≈80%)

• Architect, implement, and optimize cutting-edge control systems in modern C++ (C++17/20).
• Own the design of high-precision trajectory-tracking solutions, from formulation through production deployment.
• Identify and refine dynamic vehicle parameters using real-world data.
• Profile and optimize algorithms to meet real-time performance constraints.
• Write clean, maintainable, production-quality code and set the technical bar for the codebase.
• Analyze and iterate on system performance using real-world vehicle data.

• Provide technical direction and code/design review for a small team of 2-3 control engineers.
• Break down complex control problems into scoped workstreams and help the team sequence and prioritize them.
• Mentor engineers on MPC, optimization, and controls best practices.
• Act as the primary technical point of contact between Controls and the Planning and Hardware teams, ensuring architectural decisions stay cohesive across systems.
• Drive projects to completion, balancing team velocity with technical rigor.

What you'll need

• 6+ years of professional software engineering experience, with a track record of owning significant technical systems end-to-end.
• Expertise in modern C++.
• Deep understanding of algorithms, data structures, and software design patterns.
• Direct experience with Optimization, MPC, and system dynamics.
• Hands-on experience with data analysis and statistical methods applied to real-world sensor/vehicle data.
• Demonstrated ability to guide the technical direction of a small team while remaining a strong individual contributor.
• Exceptional communication and collaboration skills, with a focus on delivering results and driving cross-team alignment.

Nice to have

• Prior experience formally or informally leading a small engineering team or workstream.
• Digital signal processing techniques for analyzing real-world sensor data.
• Advanced knowledge of mathematics (optimization, probability, mechanics) and a proven ability to translate complex theory into production-ready algorithms.
• Relevant publications, patents, or achievements in hackathons/programming contests.
• A passion for staying at the forefront of the field, actively seeking and implementing state-of-the-art ideas to push performance beyond the current horizon.