Field ML Deployment Engineer — Vision & Edge AI

Visia

New York (NY)

Ibrido

USD 120.000 - 160.000

Tempo pieno

23 ore fa
Candidati tra i primi

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Curriculum e lettera di presentazione personalizzati, pronti da inviare.

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Vantaggi offerti da questo lavoro

Employer-paid health premiums
401(k) with company match
Equity
Unlimited PTO

Descrizione del lavoro

Visia in New York, NY is seeking a Deployment Engineer to take customer systems from initial site visits to a fully operational solution. You will manage cameras, edge compute, and site-specific models across industrial environments, with 30–50% on-site work and frequent travel to steel mills, scrap yards, and recycling plants.

You will collaborate with ML engineers, annotation teams, and Deployments Engineers to ensure high-quality production results, ship improvements, and build repeatable

Competenze

  • 2–3 years of full-time experience in a related role.
  • Hands-on experience shipping computer vision models used in production.
  • Comfortable with frequent travel to plant sites and on-site deployments.

Mansioni

  • Lead kickoff calls with customers to define success metrics.
  • Bring up cameras and edge compute on site and deploy initial models.
  • Fine-tune detection/segmentation models per site data.
  • Coordinate with annotation team and review labeling quality.
  • Package models for on-site GPUs and verify production consistency.
  • Set up dashboards and alerts used by operators.
  • Set realistic expectations and communicate progress and risks.
  • Document tooling, checks, and playbooks to accelerate future deployments.

Conoscenze

Computer vision
Field deployments
Customer-facing
Edge compute on site

Descrizione del lavoro

Visia in New York, NY is seeking a Deployment Engineer to take customer systems from initial site visits to a fully operational solution. You will manage cameras, edge compute, and site-specific models across industrial environments, with 30–50% on-site work and frequent travel to steel mills, scrap yards, and recycling plants.

You will collaborate with ML engineers, annotation teams, and Deployments Engineers to ensure high-quality production results, ship improvements, and build repeatable

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