Senior Machine Learning Engineer I

Axon•Seattle, WA

13d•$150,750 - $241,200•Hybrid

About The Position

Axon is seeking a senior Machine Learning Engineer to join a new team building agentic video and multimodal reasoning systems. The role owns the systems and infrastructure that turn research into safe, reliable, and scalable AI capabilities supporting Axon’s mission to accelerate justice, protect truth, and save lives. Working closely with research scientists, the engineer will build the data and ingest pipelines, training and evaluation infrastructure, inference and serving stack, retrieval and orchestration layers, and reliability, security, and privacy capabilities needed to bring models into production at scale. The position is based in Axon’s Seattle, Washington office and follows a hybrid schedule: onsite Tuesday through Friday, with the flexibility to work remotely on Mondays unless an approved workplace accommodation applies. The role reports to Tom Faulhaber, Director of Software Engineering, AI.

Requirements

Bachelor’s degree in Computer Science, Engineering, Physics, Mathematics, or an equivalent highly technical field.
At least 7 years of software engineering experience.
Proven track record architecting, operating, and maintaining large-scale distributed platforms in production.
Deep experience building systems across the ML lifecycle, including 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.
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 ability to work across 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 Haves

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.

Responsibilities

Own end-to-end 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, including storage, processing, labeling, and retrieval.
Build and scale training and evaluation infrastructure, turning 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 retrieval, indexing, and embedding infrastructure, including vector search at scale, as well as orchestration and tool-use systems for 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.