Machine Learning Scientist

Mental Canvas (HearstLab); United States; A distancia; USD 120.000 - 160.000; Jornada completa

Descripción de la vacante

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.

Formación

• 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.

Responsabilidades

• 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.

Conocimientos

Deep learning

Computer vision

Image synthesis

Production deployment

UI for data collection

Descripción del empleo

We are looking for a Machine Learning Scientist with experience applying deep learning methods to computer vision and image synthesis problems. The ideal candidate has a strong interest in creating and adapting user interfaces for data collection and ground-truth modeling. We value candidates who have experience deploying models in real-world applications rather than focusing solely on leaderboard performance.

Responsibilities will include:

• 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 machine learning 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

You’re a great fit if you:

• Have hands-on experience with deep learning frameworks and computer vision techniques
• Are skilled in building and deploying machine learning models in production environments
• Have a strong interest in user interface design for data collection and annotation
• Prefer practical, deployed solutions over theoretical or leaderboard results
• Are self-motivated, organized, and able to work independently or as part of a team