ML Research Engineer

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

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!)