ML Research Engineer

• Company Background
• Specter's mission is to help automate the physical world.

Today, we build video sensors with state-of-the-art AI agents that answer any question, anywhere in their environments. Our systems can automatically detect and reason about any physical activity captured on camera, from security incidents (e.g. perimeter intrusion, theft, LPR), to safety monitoring (e.g. PPE detection, injured people), to operational efficiency (e.g. material tracking, congestion monitoring). We offer both long range wireless (1km range) and wired sensor variants to suit any deployment.

Our co-founders Xerxes and Philip are passionate about empowering our partners in the fast approaching world of physical AI and robotics. We are a small, fast growing team who hail from Anduril, Tesla, Uber, and the U.S. Special Forces.

• The Role
• Specter 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!)