Senior Machine Learning Engineer I

Axon Enterprise; Seattle (WA); Hybride; USD 151 000 - 241 000; Plein temps

Avantages offerts par ce poste

Competitive salary

401k with employer match

Discretionary paid time off

Paid parental leave

Wellness programs

Employee Resource Groups (ERGs)

Snacks in office

Résumé du poste

Axon Enterprise seeks a seasoned Machine Learning Engineer to join a team building agentic video and multimodal reasoning systems. You will own the systems and infrastructure that turn cutting-edge research into safe, reliable AI capabilities supporting our mission to protect life.

As a senior engineer you will work with researchers to design data pipelines, training and evaluation infra, and scalable inference and serving stacks for production.

Qualifications

• 7+ years of software engineering in distributed production platforms.
• Experience across the ML lifecycle: data pipelines, training, inference, monitoring.
• Experience with large-scale video or multimodal data.
• Strong Python skills and ML framework familiarity (PyTorch or TensorFlow).
• Experience operating cloud infra at scale (AWS, GCP, or Azure) with containers.
• Excellent problem-solving and system-architecture focus.
• Strong collaboration with scientists, engineers, and product managers.

Responsabilités

• Own end-to-end systems and infrastructure turning research into production.
• Design data and ingest pipelines for large-scale video and multimodal corpora.
• Build training and evaluation infra and automated metrics.
• Develop real-time and batch inference/serving systems with optimized latency.
• Build retrieval, vector search, and orchestration for agentic reasoning.
• Ensure platform security, privacy, and responsible design.
• Set technical direction and mentor teammates.

Connaissances

Python

PyTorch

TensorFlow

Distributed systems

Cloud platforms (AWS/GCP/Azure)

Large-scale data processing

ML lifecycle experience

Communication with researchers

Formation

Bachelor's degree in Computer Science, Engineering, or related technical field

Outils

Docker

Kubernetes

Vector databases

Description du poste

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 and container orchestration.
• Excellent problem-solving skills and the ability to dive into system architecture, design, performance metrics, code, test plans, project plans, deployments, and operations.
• Strong communication skills and comfort partnering closely with scientists, engineers, and product managers.

Nice to Have

• Master’s or PhD in Computer Science, Engineering, or an equivalent highly technical field.
• Experience building video processing or video understanding pipelines at scale.
• Experience with retrieval systems, vector search, and RAG infrastructure.
• Experience serving foundation models, or building agentic systems and LLM tool-use orchestration.
• Familiarity with responsible AI, de-identification, and privacy-preserving techniques.

Benefits that benefit you

• Competitive salary and 401k with employer match
• Discretionary paid time off
• Paid parental leave for all
• Fitness Programs
• Emotional & Mental Wellness support
• Employee Resource Groups (ERGs)
• 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

Axon is a total compensation company, meaning compensation is made up of base pay, bonus, and stock awards. The actual base pay is dependent upon many factors, such as: level, function, training, transferable skills, work experience, business needs, geographic market, and often a combination of all these factors. Our benefits offer an array of options to help support you physically, financially and emotionally through the big milestones and in your everyday life. To see more details on our benefits offerings please visit https://www.axon.com/careers .

Base Pay Range

$150,750 - $241,200 USD

Don’t meet every single requirement? That's ok. 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. We are also committed to building diverse teams that reflect the communities we