Staff & Senior ML & CV Engineer - Grounding & Distillation

Enari Inc. (dba Verdun)

United States

Hybrid

USD 150,000 - 230,000

Full time

30 hours ago
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Job summary

Enari Inc. (dba Verdun) is seeking a Staff/Senior ML & CV Engineer to strengthen grounding, distillation, and scalable perception capabilities. You will build detection, tracking, and VLM-driven reasoning systems that operate on real-world data.

You should ship robust models, balance quality with latency and cost, and contribute to training pipelines, evaluation tooling, and end-to-end model improvements in a production setting.

Qualifications

  • Strong experience in computer vision, multimodal ML, or video understanding.
  • Shipped models that had to work on real-world data, not just benchmarks.
  • Comfortable across detection, tracking, representation learning, VLMs, and model optimization.
  • Pragmatic about balancing quality, latency, and cost in production.

Responsibilities

  • Detection and tracking models that ground higher-level reasoning.
  • VLM selection, adaptation, and fine-tuning for security incident understanding.
  • Temporal / multi-frame modeling so the system reasons over clips, not just frames.
  • Image-quality handling: ROI-aware processing, low-light enhancement, denoise, super-resolution, and keyframe selection.
  • Distillation of a lightweight first-pass model so the system stays accurate and cheap at scale.
  • Tight loop with evals: hard negatives, false positives / negatives, and operator overrides into model improvements.

Skills

Computer vision
Multimodal ML
Video understanding
Python production

Tools

Python

Job description

Enari Inc. (dba Verdun) is seeking a Staff/Senior ML & CV Engineer to strengthen grounding, distillation, and scalable perception capabilities. You will build detection, tracking, and VLM-driven reasoning systems that operate on real-world data.

You should ship robust models, balance quality with latency and cost, and contribute to training pipelines, evaluation tooling, and end-to-end model improvements in a production setting.

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