Description:

Join Axon and contribute to a mission that aims to protect life by addressing critical safety and justice issues through devices and cloud software.
As a Sr. AI Research Scientist, you will investigate research approaches, assess implementation risks, and define success metrics for multiple AI/ML projects.
Collaborate with other research scientists and machine learning engineers throughout the entire AI innovation life cycle, from model prototyping to deployment and continuous learning.
Drive one or more phases of the ML development lifecycle, including shaping datasets, investigating modeling approaches, training/evaluating/tuning models, and implementing the end-to-end training pipeline.
Leverage state-of-the-art research to deliver high-quality models that enable multiple AI projects at scale.
Contribute to the research community through academic publications, tech blogs, open-source code, and participation in AI challenges.

Requirements:

A Master’s Degree (PhD preferred) in Computer Science, Machine Learning, Statistics, Applied Mathematics, or a related technical field is required.
Hands-on experience in developing, scaling, and implementing machine learning solutions using programming languages like Python and deep learning frameworks such as PyTorch and TensorFlow is essential.
A minimum of 5 years of combined academic and industrial research experience in developing Computer Vision solutions in a business setting is required.
A track record of publications and contributions to the machine learning community is necessary.
Excellent problem-solving skills and the ability to analyze data, model architecture, learning algorithms, evaluation metrics, and testing scenarios are required.
Strong communication skills to interact with scientists, engineers, and product managers, and the ability to translate complex AI and Machine Learning concepts to a general audience are essential.
Experience with active learning, learning from synthetic data, and one-shot/data-efficient training of ML models is preferred.
Demonstrated knowledge of distributed machine learning and deploying models at scale in cloud environments such as AWS, Microsoft Azure, and Google Cloud is required.
Familiarity with IoT/Edge AI and optimizing ML models for on-device execution with constrained compute, power, and latency budgets is a plus.

Competitive salary and a 401k plan with employer match are offered.
Discretionary paid time off and paid parental leave for all employees are included.
Comprehensive medical, dental, and vision plans are provided.
Access to fitness programs and emotional & mental wellness support is available.
Opportunities for learning and development programs are offered.
Snacks are provided in the offices to enhance the workplace experience.