Senior ML Engineer — Edge Perception for Sea Autonomy

SeaSatellites, Inc.

San Diego (CA)

On-site

USD 180,000 - 250,000

Full time

14 days+

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Benefits offered by this job

Stock options
Competitive insurance
401k matching
Four free lunches per week
Employee activity fund
Pet-friendly office
Unlimited/Flex PTO

Job summary

Seasats is seeking a Senior Machine Learning Engineer to own perception-model development, training, and edge deployment for maritime autonomous vehicles. You will shepherd models from experiment to production, curate fleet data, and validate real-world performance at sea.

You will define the ML roadmap for onboard perception, run impactful experiments, and collaborate with vehicle software to integrate your work into the stack while mentoring peers and communicating complex ideas clearly.

Qualifications

  • 7+ years in ML, 5+ years perception in production
  • Deep computer vision, foundation models, small custom models
  • Ship ML models to edge devices, optimize for edge
  • Strong Python, PyTorch, OpenCV fluency
  • MLOps for dataset versioning, experiments, deployment
  • Real-time sensor data experience; fusion concepts
  • Ability to scope projects, mentor engineers, communicate well

Responsibilities

  • Define and drive the ML roadmap for vehicle perception
  • Experiment with clearly measurable end states affecting performance
  • Train, fine-tune, and optimize edge models; validate on target hardware
  • Build and maintain data pipelines from fleet data
  • Establish evaluation frameworks and metrics for model behavior

Skills

Machine learning
Perception
Edge deployment
Python
PyTorch
OpenCV
MLOps
Sensor data
Project leadership
Technical communication

Tools

TensorRT
ONNX Runtime

Job description

Seasats is seeking a Senior Machine Learning Engineer to own perception-model development, training, and edge deployment for maritime autonomous vehicles. You will shepherd models from experiment to production, curate fleet data, and validate real-world performance at sea.

You will define the ML roadmap for onboard perception, run impactful experiments, and collaborate with vehicle software to integrate your work into the stack while mentoring peers and communicating complex ideas clearly.

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