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
Field Performance & Monitoring
Define metrics and evaluation frameworks to monitor deployed system health
Investigate perception failures and drive resolution across teams
End-User Engagement
Partner with operators and customers to translate field challenges into engineering solutions
Qualifications
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
Preferred Skills
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
Why This Role Matters
You won’t just build models — you will build perception systems that operate in real-world, contested environments. Your work will directly influence the reliability, safety, and mission success of autonomous platforms deployed at sea.
Benefits
100% Employer paid Health Insurance