Skills this job asks for
Machine learningPlumbingData engineeringPythonPyTorchTensorFlowAWSGoogle CloudAzure
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Sponsorship verdict
Sponsorship possible
One solid signal, not two. Worth applying, and worth asking about sponsorship early.
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✓
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.
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The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
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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.
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What Axon Enterprise INC paid sponsored hires in similar roles38 certified filings for “Senior Software Engineer” (Software Developers) in WA: $149k–$188k, median $185k.
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Confirmed live todayWhen a source last listed this job as open.
Details and sources
- Employer is on a government sponsor record
- 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. Source: LCA disclosure data (US Department of Labor (OFLC)).
- No salary bar for this route
- H-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 roles
- 38 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).
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.
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
We are seeking a seasoned Machine Learning Engineer to join a new team building agentic video and multimodal reasoning systems. As a senior engineer on this team you will own the systems and infrastructure that turn cutting-edge research into safe, reliable, and scalable AI capabilities — supporting our company’s mission to accelerate justice, protect truth, and save lives.
Working shoulder to shoulder with research scientists, you will build everything that stands between a promising model and a production system operating on video and multimodal data at scale: the data and ingest pipelines, the training and evaluation infrastructure, the inference and serving stack, the retrieval and orchestration layers behind agentic reasoning, and the reliability, security, and privacy guarantees that Axon’s customers depend on. Scientists define the models and the metrics; you build the platform that lets them move fast and lets those models ship.
At Axon, we Aim Far. We think big with a long-term view because we want to reinvent the world to be a safer, better place. If you’re excited about this role and our mission to Protect Life but your experience doesn’t align perfectly with every qualification listed here, we encourage you to apply anyway. You may be just the right candidate for this or other roles.
What You’ll Do
Location: Seattle, WA
Reports to: Tom Faulhaber, Director of Software Engineering, AI
• Own end to end the systems and infrastructure that take multimodal and video models from research prototype to reliable, scalable production.
• Design and operate data and ingest pipelines for large-scale video and multimodal corpora — storage, processing, labeling, and retrieval.
• Build and scale training and evaluation infrastructure, and turn scientists’ evaluation methodology into automated, reproducible measurement systems.
• Build inference and serving systems for real-time and batch multimodal workloads, optimizing latency, throughput, and cost.
• Build the retrieval, indexing, and embedding infrastructure (vector search at scale) and the orchestration and tool-use plumbing behind agentic reasoning over video and multimodal data.
• Ensure the platform is secure, privacy-preserving, and responsible by design.
• Set technical direction for the team’s systems, raise the engineering bar, and mentor other engineers.
What You Bring
• Bachelor’s Degree in Computer Science, Engineering, Physics, Mathematics or an equivalent highly technical field.
• 7+ years of software engineering experience and a proven track record of architecting, operating, and maintaining large-scale distributed platforms in production.
• Deep experience building systems across the ML lifecycle: data pipelines, training and evaluation infrastructure, model serving and inference at scale, and production monitoring.
• Experience with large-scale data systems handling video or other high-volume, high-dimensional multimodal data.
• Strong software engineering fundamentals and proficiency in Python, along with familiarity with ML frameworks such as PyTorch or TensorFlow.
• Hands-on experience operating cloud infrastructure at scale (AWS, GCP, or Azure), including distributed systems an
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