Principal Software Engineer, Perception Architect

ONE STOP COLLECTIBLE CORP

United States

1 day ago

Apply on startup.jobs

Prepare application

Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Experienced

Experience required

2 years minimum

Working hours

Regular working hours

Job source

startup.jobs

Tech stack

Computing Platforms Computer Vision Python (Programming Language) Rapid Prototyping Process Sensor Fusion Deep Learning Information Technology Hardware Acceleration Lidar

Job description

System Synthesis: Define the end-to-end perception architecture-assess new sensing (LiDAR, Radar, Camera) to the final fused world model.
Hardware-Software Co-Design: Partner with Compute and Sensing teams to influence the design, ensuring our algorithms have the “computational oxygen” they need.
Algorithmic Strategy: Lead the transition from current pipelines to AI innovation pipelines, while maintaining the safety and interpretability required for edge deployment.
Future-Proofing: Evaluate emerging technologies and determine their viability for the 3-5 year roadmap.
Performance Budgeting: Collaborate on rigorous metrics for latency and accuracy across diverse edge-computing environments.
Lead cross functional teams: to create a viable plan to move to new platforms and unlock further technical capabilities for Perception systems. Coordinate projects across partner teams to make sure work is aligned with the overall org direction.

Requirements

Education: Ph.D. or MS in Computer Science, Robotics, Electrical Engineering, or a related field with a focus on Computer Vision.
Experience: 8+ years in autonomous systems with at least 2 years in an architectural role, shipping and evolving perception systems
Deep Domain Expertise: Mastery of systems focused on Computer Vision, Deep learning, Foundational models, Sensor Fusion, and State Estimation (SLAM, EKF/UKF). Deep understanding of sensor modalities and their impact to perception/autonomy systems, including: Camera, lidar, radar.
Platform Proficiency: Deep understanding of hardware acceleration, component budgeting and transition to new platforms.
Mathematical Rigor: Strong foundation in 3D geometry, linear algebra, and probabilistic robotics.
Hands on Skills: Proficiency in C++ (production-grade) and Python (rapid prototyping). Ability to run experiments across system components and run metrics platforms.
Soft Skills: Curious, Data driven, with ability to translate complex technical trade-offs to non-technical stakeholders and executive leadership.