Staff Software Engineer, Perception

SaildroneAlameda, CA
1d$189,000 - $243,000Onsite

About The Position

Saildrone is seeking a Staff Perception Engineer to join our Perception Engineering team. Reporting to the Engineering Manager, Perception, you will play a critical role in enabling real-time detection, tracking, and classification of vessels across Saildrone’s autonomous fleet. You will architect and deliver perception systems that operate reliably in complex maritime environments, directly advancing Saildrone’s mission to provide persistent maritime intelligence. We are looking for a technical expert who creates clarity from ambiguity, drives high-performance systems from concept to deployment, and thrives in solving hard autonomy problems in real-world conditions.

Requirements

  • Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, Robotics, or a related field.
  • 8+ years of experience in perception or autonomy, including 3+ years of professional C++ development for real-time embedded systems.
  • Demonstrated proficiency in Radar and Camera-based detection, GPU-accelerated computing (CUDA), and the ROS ecosystem.
  • Proven ability to solve complex tracking and classification problems in high-noise maritime environments using advanced filtering techniques (Kalman/Particle).
  • Ability to clearly communicate technical tradeoffs regarding sensor range, power consumption, and compute constraints to cross-functional stakeholders.
  • Ability to work effectively in a high-stakes R&D environment, translating ambiguous mission needs (e.g., counter-smuggling) into structured technical requirements.
  • Working knowledge of signal processing fundamentals and the deployment of ML models to resource-constrained edge devices (NVIDIA Jetson/AGX).

Nice To Haves

  • Experience with Python for prototyping, data analysis, and large-scale performance tracking preferred.

Responsibilities

  • Algorithm Development : Design, implement, and optimize perception algorithms (detect, track, classify) to achieve high-fidelity situational awareness in contested maritime environments.
  • System Architecture: Be accountable for high-performance C++ systems on NVIDIA Jetson/AGX platforms, ensuring ownership of the real-time "digital overwatch" stack.
  • Multi-Sensor Fusion: Work closely with Autonomy and ML teams to architect pipelines that fuse Radar, Camera, and AIS data, utilizing Kalman or Particle filtering to mitigate vehicle motion and wave clutter.
  • Sensor Integration: Carry out the evaluation and integration of new sensing technologies, partnering with Hardware and Systems teams to harden hardware-software interfaces for months-long deployments.
  • ML & Signal Processing : Monitor for end-to-end system performance bottlenecks, taking action to optimize GPU-accelerated signal processing and machine learning models for onboard execution.
  • Regression & Data Science: Adhere to rigorous testing standards by developing large-scale regression frameworks and using Python to analyze mission telemetry and sensor performance.
  • User Awareness : Provide timely updates and collaborate with UI/Platform engineers to ensure perception outputs are clearly visualized for remote pilots and navigational safety systems.
  • Risk & Lifecycle Management: Perform all responsibilities with a focus on hardening algorithms against environmental degradation, identifying technical risks, and driving mitigation strategies for autonomous survival.

Benefits

  • Paid time off, including vacation, bereavement, jury duty, sick time and parental leave
  • Comprehensive and competitive medical, dental and vision plans, and HSA with employer matching.
  • Company sponsored life insurance
  • Stock Options
  • Annual stipend for continued learning and development
  • Quarterly company BBQs at our Alameda HQ (bring your friends and family!)
  • Free Bay Area Public Transportation via AlamedaTMA with the BayPass Clipper Card
  • The salary range for the role is $189,000-$243,000 annually.
  • Individual compensation packages are based on geographic location, scope of the role, and relevant experience, among other factors.
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