Sr AI Research Scientist I - Machine Learning & MLLM's

At Axon, we're on a mission to Protect Life. We're explorers, pursuing society's most critical safety and justice issues with our ecosystem of devices and cloud software. Life at Axon is fast-paced, challenging and meaningful. Here, you'll take ownership and drive real change. Constantly grow as you work hard for a mission that matters at a company where you matter.

As a Sr. Research Scientist, you will investigate the research approach, assess the implementation risk and define the success metrics for multiple AI/ML projects while collaborating with other research scientists and machine learning engineers. You will be actively involved throughout the entire AI innovation life cycle from model prototyping to deployment and continuous learning. The ideal candidate will have a proven scientific background and a consistent track record of successfully researching and delivering scalable AI-based products with hands-on execution.

What You'll Do:

• 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.
• Contribute back to the research community via academic publications, tech blogs, open-source code and contributing to internal/external AI challenges

What You Bring:

• 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 (such as Python), state-of-the-art deep learning frameworks (such as PyTorch and Tensorflow) and code development and review tools (such as Github).
• 5+ years of combined academic and industrial research experience developing Computer Vision solutions (such as object detection/tracking/recognition and visual scene understanding) 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 (such as AWS, Microsoft Azure and Google Cloud).
• Familiarity with IoT/Edge AI and optimizing ML models to run on-device with constrained compute, power and latency budgets.

By accelerating the adoption of our technologies, you'll help protect life in public safety for both officers and the communities they serve around the world.