AI Research Scientist

4 weeks ago

Seattle, Washington, United States Axon Full time
Protect Life as a Sr. Research Scientist at Axon. Join our mission to reinvent the world to be a safer, better place. As a key member of our Research Science team, you will lead the development of cutting-edge AI/ML projects, shaping datasets, investigating modeling approaches, and implementing end-to-end training pipelines. You will work closely with cross-functional teams, including machine learning engineers and product managers, to deliver high-quality models that enable multiple AI projects at scale. If you are passionate about AI, Machine Learning, and making a real impact in public safety, this is the opportunity for you.

Key Responsibilities:
  • Drive one or more phases of the ML development lifecycle, including dataset shaping, modeling approaches, and end-to-end training pipeline implementation.
  • Leverage state-of-the-art research to deliver high-quality models that enable multiple AI projects at scale.
  • Collaborate with cross-functional teams to deliver models that meet product requirements and drive business impact.

What We Offer:
  • Competitive salary and 401k with employer match.
  • Discretionary paid time off.
  • Paid parental leave for all.
  • Medical, Dental, Vision plans.
  • Fitness Programs.
  • Emotional & Mental Wellness support.
  • Learning & Development programs.
  • And yes, we have snacks in our offices.

Requirements:
  • A Master's Degree (PhD preferred) in Computer Science, Machine Learning, Statistics, Applied Mathematics, or an equivalent highly technical field.
  • Hands-on experience in developing, scaling, and implementing machine learning solutions using relevant programming languages, state-of-the-art deep learning frameworks, and code development and review tools.
  • 5+ years of combined academic and industrial research experience developing Computer Vision solutions in a business setting.
  • Track record of publications and contributions to the machine learning community.
  • Excellent problem-solving skills and ability to dive into data, model architecture, learning algorithms/optimization, evaluation metrics, and testing scenarios.
  • Comfort communicating and interacting with scientists, engineers, and product managers, as well as understanding and translating the science of AI and Machine Learning to a more general audience.
  • Active learning, learning from synthetic data, and one-shot/data-efficient training of ML models.
  • Demonstrated knowledge and experience with distributed machine learning and deploying models at scale in cloud environments.

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