H

HavocAI

Affordable, scalable autonomous surface vessels

Engineering Manager - Perception and Machine Learning

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeRemote in USARemote

About the Job

Requirements

  • A bachelor's degree in Computer Science, Machine Learning, Robotics, Electrical Engineering, Computer Engineering, or a related technical field is required.
  • At least 7 years of relevant engineering experience in perception, machine learning, computer vision, robotics, autonomy, sensor fusion, or related fields is required.
  • At least 2 years of direct people-management experience, ideally managing engineers in a highly technical environment, is required.
  • Strong technical understanding of modern perception systems, including computer vision, sensor fusion, tracking, detection, classification, or machine-learning-based scene understanding, is required.
  • Experience taking machine-learning or perception capabilities from development through testing and deployment in real-world systems is required.
  • Demonstrated ability to manage engineering priorities, technical roadmaps, dependencies, and delivery across multiple initiatives is required.
  • Experience hiring, coaching, developing, and evaluating engineering talent is required.
  • Strong cross-functional leadership skills and experience partnering with software, autonomy, data, hardware, product, and field teams are required.
  • Ability to make sound decisions across technical performance, schedule, resources, risk, and product requirements is required.
  • Ability to communicate technical issues and tradeoffs to technical and non-technical stakeholders is required.
  • High ownership, sound judgment, and comfort operating in fast-moving, ambiguous environments are required.
  • U.S. citizenship and the ability to obtain and maintain a security clearance are required.

Responsibilities

  • Lead, manage, and develop a team of perception, machine learning, sensor fusion, and software engineers.
  • Own team planning, prioritization, execution, and delivery against the Perception and Machine Learning roadmap.
  • Establish clear goals, responsibilities, and expectations for the team and hold engineers accountable for results.
  • Partner with senior technical contributors to guide architecture and technical decisions across computer vision, sensor fusion, tracking, detection, classification, segmentation, and related capabilities.
  • Oversee development and maturation of model training, evaluation, data curation, validation, and deployment workflows.
  • Ensure perception capabilities are designed around real-world performance, reliability, compute constraints, and field readiness.
  • Partner cross-functionally with Autonomy, Embedded, Data, Simulation, Hardware, Product, Programs, and Field Operations.
  • Translate customer, mission, and product requirements into clear engineering priorities and execution plans.
  • Use field data, testing results, and operator feedback to prioritize improvements and address performance gaps.
  • Establish effective engineering practices around design reviews, code reviews, testing, model evaluation, release readiness, and technical documentation.
  • Identify execution risks, dependencies, resource constraints, and technical tradeoffs and communicate them clearly to engineering leadership.
  • Coach and develop engineers through regular feedback, performance management, career development, and mentorship.
  • Recruit, interview, onboard, and retain high-performing engineers as the team grows.
  • Foster a culture of technical excellence, ownership, collaboration, and continuous improvement.

Desired Qualifications

  • An advanced degree in Computer Science, Machine Learning, Robotics, Electrical Engineering, Computer Vision, or a related field is preferred.
  • Previous experience managing a Perception, Machine Learning, Robotics, or Autonomy engineering team is preferred.
  • Experience with robotics, autonomous vehicles, defense technology, aerospace, maritime systems, or other deployed autonomous systems is preferred.
  • Experience with multimodal sensor systems including cameras, electro-optical/infrared (EO/IR), radar, LiDAR, Automatic Identification System (AIS), Global Positioning System/Inertial Navigation System (GPS/INS), or inertial measurement unit (IMU) is preferred.
  • Familiarity with PyTorch, TensorRT, ONNX, CUDA, MLflow, Docker, Kubernetes, NVIDIA Jetson, or similar machine-learning and deployment technologies is preferred.
  • Experience with simulation, synthetic data, annotation workflows, and large-scale perception datasets is preferred.
  • Experience supporting field testing, customer demonstrations, operational evaluations, or deployed robotic systems is preferred.
  • Experience supporting government or Department of Defense programs is preferred.
  • An active or prior security clearance is preferred.

About the Company

HavocAI

Affordable, scalable autonomous surface vessels

HavocAI develops scalable maritime autonomy solutions, focusing on ultra-low-cost, high-rate production of Autonomous Surface Vessels (ASVs) for defense and commercial markets. Its approach enables large-scale deployment of multi-mission autonomous ships that can perform security, surveillance, logistics, and environmental monitoring tasks. The way it works is by prioritizing affordability without sacrificing capability, enabling mass production and rapid deployment of a versatile fleet. This makes HavocAI stand out from competitors by combining cost-effectiveness with high scalability, aiming to supply thousands of autonomous maritime assets. The company’s goal is to redefine how maritime autonomy is adopted and integrated worldwide through widespread, rapid deployment of affordable autonomous vessels.

Company size
201-500
Company stage
Series A
Total funding
$196M
Headquarters
East Providence, RI
Founded
2024

Recently Posted Jobs

Explore more opportunities at HavocAI

See more jobs