Senior Edge ML Engineer, Maritime Perception

Seasats; San Diego (CA); On-site; USD 180,000 - 250,000; Full time

Benefits offered by this job

Stock options

401k matching

Four free lunches per week

Employee activity fund

Pet-friendly office

Unlimited/Flex PTO

Competitive insurance

Job summary

Seasats in San Diego seeks a Senior Machine Learning Engineer to own the development, training, and edge deployment of perception models for our autonomous vessels. You will take models from experiment to production, curate fleet data, and validate them against real-world maritime conditions.

You'll lead the ML roadmap, collaborate with the vehicle software team, and iterate on data pipelines, evaluation frameworks, and model optimizations to maximize edge performance.

Qualifications

• 7+ years in machine learning with 5+ years in perception for production systems.
• Deep CV background with foundation models and smaller custom models.
• Shipping ML models to edge devices; optimizing for edge runtimes.
• Proficient in Python; expert in PyTorch; strong OpenCV knowledge.
• Experience with MLOps for dataset versioning, experiment tracking, and deployment.
• Experience with real-time sensor data (camera, radar, IMU) and fusion concepts.
• Ability to scope projects, lead technical efforts, and mentor engineers.

Responsibilities

• Help define and drive the ML roadmap for vehicle perception.
• Scope and run ML experiments with measurable end states affecting performance.
• Train, fine‑tune, and optimize models for compute‑limited edge hardware and validate on target hardware.
• Build and maintain the data pipeline from fleet data to drive development.
• Establish evaluation frameworks and metrics to validate model behavior before sea deployment.

Skills

Perception ML

Edge deployment

Python

PyTorch

OpenCV

MLOps

Real-time sensors

Model optimization

Foundation models

TensorRT

ONNX Runtime

Tools

TensorRT

ONNX Runtime

Job description

Seasats in San Diego seeks a Senior Machine Learning Engineer to own the development, training, and edge deployment of perception models for our autonomous vessels. You will take models from experiment to production, curate fleet data, and validate them against real-world maritime conditions.

You'll lead the ML roadmap, collaborate with the vehicle software team, and iterate on data pipelines, evaluation frameworks, and model optimizations to maximize edge performance.