Remote Computer Vision ML Engineer

Hired

Udine

Remoto

EUR 87.000 - 130.000

Tempo pieno

2 giorni fa
Candidati tra i primi
Generatore di candidature

Distinguiti per questo ruolo — genera un curriculum personalizzato e una lettera di presentazione in circa un minuto.

Supera i filtri ATS

Descrizione del lavoro

Hired is seeking a Python Machine Learning Engineer specialized in Computer Vision to drive the design, development, and delivery of advanced ML solutions. This remote role requires leadership to mentor the team and align ML initiatives with business goals.

You will own end-to-end ML development, from data pipelines to deployment and monitoring, collaborating with product, engineering, and business stakeholders to define problems and success metrics.

Competenze

  • Experience building end-to-end ML solutions from data pipelines to deployment.
  • Strong leadership and ability to mentor team members.
  • Ability to translate business goals into robust ML architectures.

Mansioni

  • Own end-to-end machine learning solution development, from data pipelines and model design to deployment and monitoring.
  • Translate business objectives into robust ML architectures that accurately capture business logic and context.
  • Collaborate cross-functionally with product, engineering, and business stakeholders to define problem statements and success metrics.
  • Evaluate and optimize models for performance, scalability, and accuracy using state-of-the-art techniques.
  • Stay current with advancements in AI/ML research and apply relevant innovations to improve outcomes.

Conoscenze

Python
Machine Learning
Computer Vision
Model Deployment
Data Pipelines
Technical Leadership

Descrizione del lavoro

Hired is seeking a Python Machine Learning Engineer specialized in Computer Vision to drive the design, development, and delivery of advanced ML solutions. This remote role requires leadership to mentor the team and align ML initiatives with business goals.

You will own end-to-end ML development, from data pipelines to deployment and monitoring, collaborating with product, engineering, and business stakeholders to define problems and success metrics.

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