ML Research Engineer

Specter

$130K — $180K *
Information Technology
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • 5+ years in deep learning for computer vision tasks like object detection and segmentation using PyTorch, TensorRT, and ONNX.
  • Experience with vision-language and large language models in relevant deep learning frameworks.
  • Skills in optimizing model runtime via quantization, pruning, and low-rank adaptation.
  • Proficiency in building production-grade RAG pipelines and scaling vector databases.
  • Strong C++/Rust development skills for embedded systems; Linux fundamentals knowledge required.
  • Solid understanding of CUDA fundamentals.
  • Experience with image/video processing and familiarity with different video codecs.
  • Experience with various sensor types, particularly EO and IR cameras.

Responsibilities

  • Implement and deploy deep-learning based vision and language models within the perception system.
  • Build and scale data collection, labeling, and model re-training platforms.
  • Drive design for a multimodal software user interface.

Benefits

  • Collaborative environment with a passionate team from leading tech companies.
  • Opportunity to work at the forefront of physical AI and robotics innovation.
  • A chance to significantly impact American business security and operational efficiency.
Full Job Description
The RoleSpecter is hiring a perception AI engineer responsible for turning sensor data pipelines into actionable insights for our customers.

Responsibilities:
  • Implementing and deploying a variety of deep-learning based vision, vision-language, and large language models to our world-class distributed perception system
  • Building and scaling a production-grade data-collection, labelling, and model re-training platform
  • Driving the design behind a multimodal software user interface


Qualifications:
  • 5+ years of experience training, implementing, and deploying deep-learning based computer vision models in tasks such as object detection, semantic segmentation, object tracking, etc. (both single and multi-frame) in frameworks such as PyTorch, TensorRT, and ONNX
  • Experience fine-tuning, implementing, and deploying vision-language models and large language models in frameworks such as PyTorch, TensorRT-LLM, and ONNX
  • Experience optimizing model runtimes utilizing techniques such as quantization, pruning, low-rank adaptation, etc. where appropriate
  • Experience building production-grade RAG pipelines, and scaling vector databases in production
  • Strong experience in C++/Rust development in embedded systems and knowledge of Linux fundamentals
  • Strong knowledge of CUDA fundamentals
  • Experience with image/video processing, filtering, and enhancement. Knowledge of various video codecs desirable.
  • Experience with variety of sensor types such as EO and IR cameras
  • Familiarity with Rust (or ability to come up the curve quickly!)

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