Remote CV Engineer - Data Workflows & Fine-Tuning

Simuletic

United States

Remote

USD 120,000 - 180,000

Full time

14 days+

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Benefits offered by this job

Remote role
GPU access
Customer feedback

Job summary

Simuletic seeks a skilled computer vision engineer to build and improve data-generation and model-evaluation workflows for security, defense and robotics applications. You will oversee the full cycle—from generating and annotating examples to training models, measuring performance and refining pipelines—in a small team with direct input into what ships.

You will create ComfyUI workflows, fine-tune LoRA models on domain data, train and benchmark YOLO detectors and vision-language or

Qualifications

  • Strong Python and PyTorch skills.
  • Experience training, fine-tuning and deploying YOLO models, version 8 or later.
  • Familiarity with vision transformers and vision-language models.
  • Ability to build and modify ComfyUI workflows.
  • Experience fine-tuning LoRAs with SDXL, Flux or comparable models.
  • Working knowledge of YOLO and COCO annotation formats.

Responsibilities

  • Create and maintain ComfyUI workflows for generating training data across relevant scenarios.
  • Fine-tune LoRA models on domain data such as equipment, vehicles and environments.
  • Train and benchmark YOLO detectors and vision-language or vision transformer models using synthetic and real data.
  • Compare model performance on generated and real-world data, then use findings to improve generation quality and dataset coverage.
  • Build fine-tuning workflows for vision-language tasks such as captioning, grounding and classification.
  • Maintain annotation accuracy and dataset quality as work is released.

Skills

Python
PyTorch
Vision transformers
Computer vision

Tools

ComfyUI
YOLO (v8+)
CUDA
ONNX/TensorRT

Job description

Simuletic seeks a skilled computer vision engineer to build and improve data-generation and model-evaluation workflows for security, defense and robotics applications. You will oversee the full cycle—from generating and annotating examples to training models, measuring performance and refining pipelines—in a small team with direct input into what ships.

You will create ComfyUI workflows, fine-tune LoRA models on domain data, train and benchmark YOLO detectors and vision-language or

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