ML Research Engineer

The role

This person will implement and deploy deep-learning based vision, vision-language, and large language models to a distributed perception system. They will build a production-grade data platform and drive the design of a multimodal software user interface.

What you will do

• Implementing and deploying deep-learning based vision, vision-language, and large language models to a 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

Required 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. in frameworks su
• 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.
• 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
• Experience with variety of sensor types such as EO and IR cameras

Nice to have

• Knowledge of various video codecs
• Familiarity with Rust (or ability to come up the curve quickly!)

About the company

Specter's mission is to help automate the physical world. They build video sensors with state-of-the-art AI agents.