ElastixAI

AI Inference Infrastructure Software Engineer (Kubernetes / Cloud)

Seattle

Sponsorship not specifiedDetected 78 days ago

PythonGoBashAWSGCPKubernetesTerraformAnsibleLinuxSite Reliability EngineeringMachine Learning

About the role

If you're excited about pushing AI performance to physical limits and shaping the future of large-scale inference, we'd love to meet you.
This is a hands-on role with broad surface area.

Build, operate, and evolve ElastixAI's Kubernetes infrastructure powering our Token-as-a-Service capability.
Manage and harden our AWS, GCP, and on-prem infrastructure, including networking, storage, IAM, and observability layers tied to our services.
Develop tooling and automation in Python, Bash, Rust, and Go to streamline deployments, rollouts, autoscaling, and incident response.
Partner with the ML and runtime teams to productionize new inference capabilities, model deployments, and routing strategies.
the best performance comes from holistic co-design, where every layer, from model architecture to kernels to silicon, works in harmony.

3-5 years of hands-on Kubernetes experience, including EKS, GKE, and/or self-hosted clusters.
2-3 years of production experience operating workloads on AWS or GCP.
Proven track record running ML or inference services at scale on Kubernetes in production.
Solid coding skills in Python, Bash and proficiency in Go
Experience with infrastructure-as-code (Terraform, Pulumi), OS configuration state (Ansible, Puppet, Salt) and GitOps workflows (Argo CD, Flux).
Experience in OS configuration tooling.
Familiarity with AI inference and/or training workflows and the operational patterns around them.

MS/PhD in Computer Science, Software Engineering, or a related field.
Experience with inference servers and runtimes (e.g., Triton, vLLM, TGI) and model-serving patterns (batching, streaming, KV-cache aware routing).
Exposure to heterogeneous accelerators beyond GPUs (FPGAs, custom ASICs).
Background in observability, SRE, or performance engineering for latency-sensitive services.

The opportunity to work on challenging problems at the intersection of ML, software, and systems.
Competitive compensation and startup equity package
Comprehensive medical, dental, and vision coverage (premiums 100% paid by employer)
Flexible Time Off (FTO)
Paid parental leave
Gym or fitness benefit
Commuter benefit
Investment in employee learning & development

Help define the platform roadmap as we scale from early customers to broad production deployments.

This listing is sourced directly from ElastixAI's careers page and normalized into a canonical job model.