Role OverviewWe're looking for a Staff or Senior ML Engineer to own the technical backbone of how AZX serves and evaluates models at scale. This is a high-leverage IC role spanning our inference platform — GPU scheduling, autoscaling, and serving infrastructure for vLLM/SGLang across cloud and customer-managed clusters — and the evaluation systems that tell us whether model, prompt, and agent changes that make things better.
What You Will Do
You'll create technical direction for how AZX serves models reliably. This role suits someone who wants architectural ownership over hard ML infrastructure problems, paired with the judgment to build the guardrails that let the rest of the team move fast safely.
Why It Might Be a Fit
You'll work on software projects in client engagements, and over time, internal platform capabilities. You'll collaborate across the gateway, sandbox, and inference platform teams, flexing across areas as priorities shift.
Requirements
- 4+ years of experience in backend engineering fundamentals: distributed systems, API design, and production experience in Go, Rust, or async Python.
- Familiarity with LLM-specific backend concerns (rate limiting, caching, token accounting) is a plus, though not required on day one.
- Exposure to Kubernetes and containerization; interest in sandboxing or security is a plus.
- Comfort working across a range of platform concerns rather than one narrow specialty — this role is intentionally broader than our specialist infra profiles.
- Eagerness to grow into deeper specialization in gateway, sandbox, or inference infrastructure over time.
Benefits
- Competitive early-stage startup compensation (based on capabilities, experience, and location)
- Bonus eligibility
- Health insurance with meaningful coverage for dependents
- Flexible paid time off
- Equity
- Fully remote culture with a cluster of teammates in Seattle
- Training and learning opportunities
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