Applied ML Scientist - Computer Vision & Production

Mental Canvas (HearstLab); United States; Remote; USD 120,000 - 160,000; Full time

Job summary

Mental Canvas (HearstLab) is seeking a Machine Learning Scientist to apply deep learning methods to computer vision and image synthesis challenges. The role emphasizes creating and adapting interfaces for data collection and ground-truth modeling, with a focus on real-world deployment rather than leaderboard performance.

Ideal candidates will have hands-on experience with deep learning frameworks and CV techniques, and a track record of deploying models in production.

Qualifications

• Hands-on experience with deep learning frameworks and computer vision techniques.
• Experience building and deploying ML models in production environments.
• Interest in user interface design for data collection and annotation.
• Preference for deployed solutions over leaderboard results.
• Self-motivated, organized, and able to work independently or in a team.

Responsibilities

• Develop and implement deep learning models for computer vision and image synthesis tasks.
• Design and adapt user interfaces to facilitate data collection and ground-truth modeling.
• Collaborate with cross-functional teams to integrate ML solutions into products.
• Evaluate and improve model performance based on real-world deployment and user feedback.
• Stay current with advancements in deep learning, computer vision, and related fields.

Skills

Deep learning

Computer vision

Image synthesis

Production deployment

UI for data collection

Job description

Mental Canvas (HearstLab) is seeking a Machine Learning Scientist to apply deep learning methods to computer vision and image synthesis challenges. The role emphasizes creating and adapting interfaces for data collection and ground-truth modeling, with a focus on real-world deployment rather than leaderboard performance.

Ideal candidates will have hands-on experience with deep learning frameworks and CV techniques, and a track record of deploying models in production.