Embedded Perception Engineer
- Compensation
- $150K–$185K / yr
- Location
- Remote
- Work setup
- Remote
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 3+ years
- Category
- Embedded
- Posted
Skills
Must have
- Bachelor’s or higher in Computer Science, Electrical Engineering, Robotics, Machine Learning, or related field
- 3+ years developing and deploying computer vision or perception systems in C++ and/or Python on Linux
- Experience with modern deep learning frameworks (PyTorch, TensorFlow)
- Hands-on experience with large vision models (ViT, CLIP, SAM, etc.)
- Experience implementing sensor fusion across heterogeneous modalities
- Proficiency with NVIDIA Triton, TensorRT, ONNX Runtime, or equivalent inference tooling
- Ability to quickly navigate and understand complex codebases
- Strong systems-thinking mindset
- U.S. Citizenship and eligibility for U.S. security clearance
Nice to have
- Experience deploying perception systems on embedded platforms (Jetson, FPGA, similar)
- Familiarity with maritime or aerial sensor environments
- Experience optimizing models for edge inference
- Knowledge of autonomy frameworks (ROS2, MOOS-IvP)
- Experience with safety-critical or real-time systems
- Familiarity with military systems and defense acquisition processes
Full description
About Us:
Havoc is a leader in all-domain collaborative autonomy. Its software-defined hardware approach powers military and commercial-grade autonomous systems across sea, air, and land to sense, decide, and act together in complex and contested environments. Havoc connects assets, enabling them to share information, adapt in real time, and continue operating even when communications are disrupted or denied. Havoc optimizes mission performance and minimizes human risk.
Havoc was founded in 2024 and headquartered in Providence, Rhode Island. Learn more at Havoc: All-Domain Collaborative Autonomy .
About the Role:
As an Embedded Perception Engineer, you will own how our autonomous systems perceive and understand the world — in real time, in operational environments, and under demanding maritime conditions.
This role goes beyond model training. You will architect, deploy, and optimize perception pipelines that run reliably on embedded edge hardware. You’ll work across vision models, sensor fusion, and high-performance inference to deliver robust situational awareness to autonomous surface vessels executing real-world missions.
If you thrive in dynamic environments, enjoy squeezing maximum performance from embedded AI systems, and want to see your work field-tested and mission-proven, this role offers immediate and meaningful impact.
Key Responsibilities and Requirements:
Perception System Ownership
- Own end-to-end perception pipelines deployed to operational systems
- Deliver high-reliability solutions aligned with mission requirements
Vision Model Development
- Design, train, and optimize perception models for maritime environments
- Develop object detection, classification, and tracking systems
- Work with large vision models (ViT, CLIP, SAM, or similar)
Sensor Fusion & Integration
- Fuse multi-modal sensor data (camera, radar, lidar) into unified perception outputs
- Collaborate with hardware teams to select and integrate sensors
- Develop and validate low-level sensor drivers for high-integrity data pipelines
Embedded Deployment & Optimization
- Deploy models using NVIDIA Triton Inference Server
- Optimize inference for latency and throughput on edge hardware
- Apply quantization, pruning, and other optimization techniques
Cross-Team Collaboration
- Integrate perception outputs into autonomy stacks alongside mission software and platform teams
- Support troubleshooting of perception performance in operational environments