Senior Machine Learning Engineer

Your Impact

Are you excited to build AI products that solve meaningful, real-world problems and make a positive impact at scale?

As a Machine Learning Engineer at Axon, you’ll help build AI solutions that are transforming public safety and advancing our mission to Protect Life. You’ll work alongside talented ML engineers and scientists to bring new AI capabilities to products such as Fleet, Draft One, Axon Air, VR, and more—supporting the training, evaluation, testing, and deployment of machine learning models across Axon devices and the cloud.

You’ll be part of a multidisciplinary team tackling challenging problems across a broad range of AI domains, from computer vision and speech recognition to natural language understanding and generative AI. You’ll work at the intersection of cutting-edge research and real-world product development, where AI systems need to be accurate, scalable, secure, responsible, and dependable in the moments that matter.

This role also offers significant room to grow your technical scope and influence. You’ll have opportunities to explore emerging AI technologies, work across multiple product areas, learn from experienced engineers and scientists, and take ownership of increasingly complex systems. As the team and Axon’s AI capabilities grow, you’ll have the opportunity to shape technical direction, mentor others, and develop into a technical leader.

What You’ll Do

Location: Hybrid from our office in Seattle, Washington.
Reports to: Manager, Machine Learning Engineering

• Turn emerging AI research into real products. Partner with scientists, engineers, and product managers to rapidly prototype new ideas, build proof-of-concepts, and help determine which technologies can become the next generation of Axon AI experiences.
• Build AI systems that operate at real-world scale. Architect and develop the infrastructure needed to train, evaluate, deploy, monitor, and continuously improve models running across Axon’s cloud and device ecosystem.
• Work across the modern AI stack. Tackle engineering challenges spanning model training and fine-tuning, large-scale evaluation, inference optimization, data pipelines, cloud infrastructure, and production ML systems.
• Help build the platform behind Axon AI. Design reusable platforms, infrastructure, and developer tooling that make it faster and easier for scientists and engineers to experiment, evaluate ideas, and move models from research into production.
• Advance how we build with generative AI. Explore techniques for evaluating, fine-tuning, optimizing, and operating large models, including approaches such as model distillation, quantization, and scalable evaluation.
• Solve challenging edge-and-cloud ML problems. Help bridge the gap between powerful cloud-based AI and models running in resource-constrained environments, balancing model quality, latency, reliability, privacy, and cost.
• Build secure and privacy-preserving AI systems. Architect solutions that enable models to continuously improve while maintaining rigorous standards for security, privacy, and responsible use of data.
• Collaborate closely with ML scientists. Translate state-of-the-art research into robust engineering systems and help develop new training, evaluation, and deployment techniques that can be applied across multiple Axon products.
• Own meaningful technical problems end to end. Go beyond implementing individual features—you’ll have opportunities to influence architecture, make key technical decisions, and see your work progress from an early experiment to technology used in real products.
• Raise the engineering bar. Help establish best practices for ML engineering, architecture, testing, observability, reproducibility, and responsible AI as Axon’s AI organization continues to scale.

Grow Your Career at Axon

• Expand your AI breadth. Work across computer vision, speech, NLP, generative AI, edge ML, and cloud ML infrastructure rather than being limited to a single model or domain.
• Deepen your technical expertise. Take on difficult systems problems at the intersection of machine learning, distributed systems, cloud infrastructure, and production software engineering.
• Grow your ownership and influence. Progress from owning individual systems to shaping architectures, technical roadmaps, and engineering practices used across teams and products.
• Learn across disciplines. Work closely with ML scientists, product teams, and experienced engineers, gaining exposure to both advanced research and the realities of shipping AI at scale.
• Build technical leadership. As you grow, you’ll have opportunities to mentor engineers, lead technical initiatives, influence cross-team decisions, and help define how AI is built at Axon.

What You Bring

• Bachelor’s degree in Computer Science, Engineering, Electronics, Mathematics, or another highly technical field.
• 6+ years of software engineering experience, including a proven track record of deploying AI/ML models to production in the cloud.
• Strong experience with cloud architecture and infrastructure as code.
• Proficiency in Python and C++, with experience using ML frameworks such as PyTorch or TensorFlow.
• Advanced, hands-on knowledge of Linux environments and systems.
• Strong problem-solving skills and the curiosity to dive deep into complex system architectures.
• Excellent software architecture and design skills, with a focus on building robust, scalable, maintainable systems.
• Ability to communicate effectively and collaborate across disciplines with scientists, engineers, and product managers.

Preferred

• Master’s degree or PhD in Computer Science, Engineering, Electronics, Mathematics, or another highly technical field.
• Experience with LLMOps, including model evaluation, monitoring, quantization, distillation/teacher-student approaches, and production deployment.
• Hands-on experience fine-tuning and optimizing large-scale models.
• Familiarity with model encryption, privacy-preserving machine learning, and secure AI techniques.

Benefits that Benefit You

• 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

Benefits listed herein may vary depending on the nature of your employment and the location where you work

Location: This role is based out of our Seattle, WA office and follows a hybrid schedule. We rely on in-person collaboration and ask that team members work onsite Tuesdays through Fridays, with the flexibility to work remotely on Mondays, unless there is an approved workplace accommodation. We believe that connection fuels innovation, and our in-office culture is designed to foster meaningful teamwork, mentorship, and shared success.

#LI-Hybrid