Director of Artificial Intelligence

Axon•Seattle, WA

11h•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 As a Director of Machine Learning Engineering you will report directly to Axon’s VP of Engineering for Dedrone and be a critical member of the Dedrone Leadership team. You will be tasked with leading machine learning platform initiatives to harness Dedrone's vast and growing network of sensors, signals, and data to provide measurably differentiated outcomes for our public safety customers and the communities they serve. As a machine learning engineering thought leader and key partner in Dedrone’s product and technology organization, you will identify key strategic opportunities and define, grow, lead, and retain a world-class team of ML Platform engineers. The ideal candidate will have a proven software engineering and scalable distributed systems architectural background as well as a consistent track record of success with hands-on execution and demonstrated ability to manage machine learning platform engineering teams. You will actively collaborate with peer engineering, science and product teams to ship and operate services at scale. We need someone willing to be bold and more than willing to take on challenges. By accelerating adoption of our technologies, you'll help protect life in public safety for officers and the communities they serve around the world.

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 building highly available, low latency systems for high traffic applications
6+ years in a leadership/management role with a solid track record of building and leading engineering teams
Fluency in Scala (or Java) as well as prior experience working with machine learning workflows in python
Designed and built multiple complex, scalable, high throughput, low latency streaming/batch processing machine learning pipelines for both data flows and algorithm execution
Advanced knowledge and hands-on experience with major cloud environments (such as AWS, Microsoft Azure and Google Cloud)
Exemplary 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
12+ years of software engineering experience building and shipping data science AI enabled products
Demonstrated knowledge and experience with machine learning platforms from major providers (such as AWS, Microsoft Azure and Google Cloud)
Experience with IoT/Edge AI and optimizing ML pipelines to run on-device with constrained compute, power and latency budgets
Previous experience leading multiple geographically distributed teams

Responsibilities

Operate as a thought leader and visionary, with the ability to guide, influence and inspire peak performance, innovation and adoption of the latest engineering practices to enable AI technologies across the Axon value chain .
Grow and lead a world-class team of machine learning platform engineers that deliver novel, strategic AI-enabled solutions with diverse, industry-leading skills in distributed machine Learning training workflows, edge AI, data engineering and tools both in the cloud and on-device.
Collaborate with science, tech and product teams on defining, architecting and building data ingestion systems and model training pipelines from experimentation to deployment, monitoring and continuous performance improvement.
Bring your industry expertise to challenge existing assumptions and introduce new distributed system architectures including high-throughput machine learning training pipelines and low-latency model hosting technologies
Develop a collaborative and inclusive team that fosters a culture of ownership, experimentation, and innovation while joining forces with product teams to deliver working solutions for our Customers