AI Scientist I

Axon Axon · Enterprise · Office, WA · 2014 Artificial Intelligence

Seeking an AI Scientist with a PhD and 1 year of experience in Computer Science and Robotics, focusing on MLLMs, Computer Vision, and Machine Learning for cloud, devices, and robotics. The role involves researching and developing advanced MLLMs and Computer Vision techniques, optimizing algorithms for resource-constrained devices, and collaborating with cross-functional teams. Responsibilities include designing, implementing, and evaluating MLLM models, contributing to publications, and mentoring junior scientists.

What you'd actually do

  1. Research and develop advanced MLLMs, GenAI, and Computer Vision techniques for cloud, devices and sensors from multimodal data sources.
  2. Design and implement efficient and scalable MLLM models for inference and analysis of visual data.
  3. Explore novel approaches to address challenges in object detection, recognition, tracking, segmentation, and scene understanding.
  4. Optimize algorithms for performance, memory footprint, and energy efficiency to meet the requirements of resource-constrained devices.
  5. Join force with MLEs or firmware or hardware engineers to leverage hardware accelerators and optimize algorithms for specific hardware architectures.

Skills

Required

  • Python
  • C/C++
  • TensorFlow
  • PyTorch
  • Keras
  • ROS
  • Computer Vision
  • Machine Learning
  • Deep Learning
  • MLLMs
  • GenAI

Nice to have

  • Experience in developing computer vision algorithms for resource-constrained devices
  • Experience with robotic operational system
  • Experience coach and mentor junior scientists

What the JD emphasized

  • PhD and 1 years experience in Computer Science and Robotics or a related field with a focus on robotics perception, MLLMs, computer vision, machine learning, or artificial intelligence.
  • Drive one or more phases of the ML development lifecycle: shape datasets, investigate modeling approaches and architectures, train/evaluate/tune models and implement the end-to-end training pipeline.
  • Leverage state-of-the-art research to deliver high quality models enabling multiple AI projects at scale.

Other signals

  • MLLMs
  • Computer Vision
  • Robotics
  • GenAI