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Havoc AI is a leader in all-domain collaborative autonomy, developing software-defined hardware for military and commercial-grade autonomous systems across sea, air, and land. Founded in 2024 and headquartered in Providence, Rhode Island, Havoc enables assets to sense, decide, and act together in complex and contested environments while maintaining operation when communications are disrupted or denied.
As Engineering Manager, Perception & Machine Learning, you will lead the team responsible for developing perception and machine learning capabilities that enable Havoc's autonomous systems to understand and operate within their environment. This is a people leadership and technical management role requiring a strong foundation in perception, machine learning, computer vision, sensor fusion, or robotics.
Key responsibilities include:
- Leading, managing, and developing a team of perception, machine learning, sensor fusion, and software engineers
- Owning team planning, prioritization, execution, and delivery against the Perception & ML roadmap
- Establishing clear goals, responsibilities, and expectations while holding engineers accountable
- Partnering with senior technical contributors to guide architecture and technical decisions across computer vision, sensor fusion, tracking, detection, classification, and segmentation
- Overseeing development and maturation of model training, evaluation, data curation, validation, and deployment workflows
- Ensuring perception capabilities are designed around real-world performance, reliability, compute constraints, and field readiness
- Translating customer, mission, and product requirements into clear engineering priorities and execution plans
- Using field data, testing results, and operator feedback to prioritize improvements
- Establishing effective engineering practices around design reviews, code reviews, testing, model evaluation, and technical documentation
- Identifying execution risks, dependencies, and resource constraints and communicating them to engineering leadership
- Coaching and developing engineers through regular feedback, performance management, and mentorship
- Recruiting, interviewing, onboarding, and retaining high-performing engineers
- Fostering a culture of technical excellence, ownership, collaboration, and continuous improvement
- Working cross-functionally with Autonomy, Embedded, Data, Simulation, Product, Programs, and Field Operations teams
Requirements:
- Bachelor's degree in Computer Science, Machine Learning, Robotics, Electrical Engineering, Computer Engineering, or related technical field
- 7+ years of relevant engineering experience in perception, machine learning, computer vision, robotics, autonomy, sensor fusion, or related fields
- 2+ years of direct people-management experience, ideally managing engineers in a highly technical environment
- Strong technical understanding of modern perception systems, including computer vision, sensor fusion, tracking, detection, classification, or ML-based scene understanding
- Experience taking ML or perception capabilities from development through testing and deployment in real-world systems
- Demonstrated ability to manage engineering priorities, technical roadmaps, dependencies, and delivery across multiple initiatives
- Experience hiring, coaching, developing, and evaluating engineering talent
- Strong cross-functional leadership skills and experience partnering with software, autonomy, data, hardware, product, and field teams
- Ability to make sound decisions across technical performance, schedule, resources, risk, and product requirements
- Strong communication skills with ability to communicate technical issues and tradeoffs to both technical and non-technical stakeholders
- High ownership, sound judgment, and comfort operating in fast-moving, ambiguous environments
- U.S. citizenship and ability to obtain and maintain a security clearance
Preferred qualifications include advanced degree in related field, previous experience managing a Perception/ML/Robotics/Autonomy engineering team, experience with robotics or autonomous vehicles, multimodal sensor systems (cameras, EO/IR, radar, LiDAR, AIS, GPS/INS, IMU), familiarity with PyTorch, TensorRT, ONNX, CUDA, MLflow, Docker, Kubernetes, NVIDIA Jetson, experience with simulation and synthetic data, field testing support, government/DoD program experience, and active or prior security clearance.
