Jobs / United States / Axon Enterprise INC
Senior Machine Learning Engineer
Axon Enterprise INC · 🇺🇸 Seattle, Washington, United States
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 117 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 19 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Axon Enterprise INC paid sponsored hires in similar roles38 certified filings for “Senior Software Engineer” (Software Developers) in WA: $149k–$188k, median $185k. Most were filed at wage level III (41%) — 3 lottery entries, ≈46% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
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Sponsor Radar — Axon Enterprise INC
The US Department of Labor certified 117 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 19 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Axon Enterprise INC →
About the role
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 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 a