Applied ML Engineer (AI)

TL;DR

Applied ML Engineer (AI): Building and optimizing machine learning models for edge-intelligent maritime systems with an accent on computer vision, sensor fusion, and lightweight inference pipelines. Focus on designing robust AI solutions for embedded hardware, managing end-to-end model lifecycles, and ensuring reliability in challenging field conditions.

Location: Hybrid (Arlington, VA; Boston, MA; or San Francisco, CA)

Company

hirify.global develops edge-intelligent maritime systems powered by advanced machine learning and perception technologies.

What you will do

• Design, train, and evaluate models for object detection, classification, and anomaly detection.
• Optimize model architectures and inference pipelines for performance on embedded hardware.
• Contribute to dataset development, synthetic data generation, and domain adaptation strategies.
• Implement real-time pipelines for processing sensor data on-device and in cloud environments.
• Support prototyping across computer vision, signal processing, and multi-modal fusion.
• Develop benchmarking, visualization, and debugging tools for ML model performance.

Requirements

• Must be eligible to obtain/maintain a security clearance.
• Master’s or PhD in Computer Vision, Machine Learning, Robotics, or a related field.
• 4+ years of experience building and deploying machine learning models in production.
• Proficiency in Python and deep learning frameworks like PyTorch or TensorFlow.
• Experience with edge/embedded ML deployments, including model compression and hardware-aware optimization.
• Strong debugging, experimentation, and problem-solving skills.

Nice to have

• Experience in maritime, aerospace, or remote sensing domains.

Culture & Benefits

• Opportunity to work on innovative projects with global impact.
• Flexible working hours with high-availability periods during deadlines.
• Collaborative environment working across hardware, software, and product teams.