Senior Machine Learning Engineer II

Axon•Washington, DC

3h•Hybrid

About The Position

Join Axon and be a Force for Good. 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. Like our products, we work better together. We connect with candor and care, seeking out diverse perspectives from our customers, communities and each other. 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. Your Impact Are you passionate about AI? Do you love engineering solutions enabling fast, cutting-edge science? Are you eager to contribute to building products impacting the world for the greater good? As a ML Engineer at Axon, you will contribute to architecting and implementing the platform used by Axon scientists to bring safe, secure, reliable AI features to Axon devices. Collaborating closely with scientists and device engineers, you will enable new AI capabilities for Axon products (Fleet, Axon Body, Axon Air, and more). You will also make sure As part of a multidisciplinary team, you will be exposed to a wide range of domains and applications: from Automatic License Plates Recognition to Object Tracking and Automatic Speech Recognition. The ideal candidate will have a consistent track record of successfully optimizing models for the edge and deploying AI models at the edge, including on device with limited memory & connectivity, to serve users world wide. They will understand the AI lifecycle and be capable of supporting scientists end-to-end along the development of a new machine learning models and AI capabilities, leading to better and more responsible AI solutions. They are willing to be bold and stand up to support the team in enabling features transforming the life of officers, and driving a positive impact in the public safety space.

Requirements

Bachelor’s Degree in Computer Science, Engineering, Physics, Mathematics or an equivalent highly technical field.
10+ years of software engineering experience and a proven track record of successfully architecting and maintaining large-scale distributed platforms.
Experience with AI on chips, on device model deployment and management.
Proficiency in python, C++, familiarity with ML frameworks such as TensorFlow, or PyTorch.
Advanced knowledge and hands-on experience with on chips development.
Excellent problem solving skills and ability to dive into system architecture, design, performance metrics, code, test plans, project plans, deployments and operations
Comfort communicating and interacting with scientists, engineers and product managers.

Nice To Haves

Master’s Degree in Computer Science, Engineering, Physics, Mathematics or an equivalent highly technical field.
Hands-on experience in solving Computer Vision or Natural Language Understanding problems in a business setting.
Familiarity with responsible AI, de-biasing, model encryption and de-identification techniques.

Responsibilities

Architect and develop secure, privacy-preserving, on device solutions to enable the continuous improvement of existing AI models.
Collaborate with scientists in architecting and implementing state-of-the-art edge distributed training techniques.
Implement on device monitoring solutions used for continuous model improvement
Implement innovative model compression solutions to enable AI at the edge.
Impact the team by bringing your own expertise and deep knowledge of the state-of-the-art to introduce new techniques leading to tangible impact in terms of model fairness, performance, and platform scalability.