Senior Computer Vision Engineer - Edge-Deploy Safety ML

Lumenalta (formerly Clevertech)

United States

Remote

USD 140,000 - 190,000

Full time

11 days ago
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Job summary

Lumenalta is seeking a Senior Computer Vision Engineer to lead end-to-end development of an enterprise workplace safety and compliance detection pipeline. You will design, train, calibrate and deploy production CV models that turn raw camera footage into actionable insights for reviewers and clients.

Fully remote in US time zones. The role blends hands-on ML engineering with client-facing leadership, building pipelines that scale from cloud batch to edge inference and optimizing for compute cost

Qualifications

  • 5+ years in applied machine learning with real-world production experience.
  • 3+ years in computer vision shipped to production on real footage.
  • Experience with YOLO, Faster R-CNN, RT-DETR or RF-DETR detectors.
  • Strong knowledge of dataset construction and evaluation fundamentals.
  • Data governance and client confidentiality awareness.

Responsibilities

  • Build end-to-end detection and tracking pipelines from video to insights.
  • Lead dataset construction with labeling guidelines and splits.
  • Train, calibrate and evaluate models against contractual targets.
  • Architect deployment options for cloud and edge inference.
  • Provide outputs consumable by reviewers and dashboards.
  • Engage with stakeholders and transfer capability.

Skills

Python
PyTorch
Distributed processing

Tools

Databricks
Spark
YOLO
Faster R-CNN
RT-DETR
RF-DETR
DeepSORT

Job description

Lumenalta is seeking a Senior Computer Vision Engineer to lead end-to-end development of an enterprise workplace safety and compliance detection pipeline. You will design, train, calibrate and deploy production CV models that turn raw camera footage into actionable insights for reviewers and clients.

Fully remote in US time zones. The role blends hands-on ML engineering with client-facing leadership, building pipelines that scale from cloud batch to edge inference and optimizing for compute cost

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