Senior Machine Learning Engineer / Staff ML Engineer

About AZX Our mission is to accelerate positive impact in critical industries through AI transformation. We’re growing quickly and already work with category-leaders in real estate (CBRE), energy (LevelTen Energy), logistics (Flexe) and utilities (can’t say which large utility yet). We’re a public benefit corporation, founded in 2024 and have been profitable from the beginning (bootstrapped with consulting). We work on challenges in clean energy, decarbonization, climate risk, energy systems and global economics. We’re building our company for long term success and aim to build the ultimate place to work if you’re passionate about AI and positive impact. About The Role We'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. 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. What You Will Do You will work on software projects in client engagements, and over time, internal platform capabilities. You will: Build and maintain backend services for our LLM gateway — routing, rate limiting, key management, and observability in front of the inference fleet. Contribute to sandboxing and isolation infrastructure that keeps agent-generated code safe to execute, working alongside our security-focused engineers. Support Kubernetes-based platform services, including operators and autoscaling logic adjacent to our inference platform. Write high-performance backend code in Go, Rust, or async Python (FastAPI/Starlette), working with infrastructure like Envoy and gRPC. Instrument services with OpenTelemetry so behavior, latency, and cost stay observable as the platform scales. Collaborate across the gateway, sandbox, and inference platform teams, flexing across areas as priorities shift. Core Qualifications - Technical And Foundational 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. Values And Culture Qualifications High emotional intelligence and a learning mindsetStrong collaboration skillsEnjoy others' success and a fun, positive environment. Comfortable making decisions in the face of ambiguity and course correcting as needed. Bonus Qualifications (not Required But a Huge Plus) Experience in both startup and enterprise environmentsPast work in energy, real estate, utilities, climate or related fieldsBonus if you have experience and passion in one or more ofAdditional web frameworks (e.g. Svelte, Vue, Angular)Lower-level languages e.g. C++, RustNetworking paradigms e.g. GraphQL, WebsocketsML capabilities e.g. Sk-learn, xgboost, Pytorch/Tensorflow/JAX, Onnx…Additional database types such as graph or vector databasesDevOps e.g. CI/CD pipelines, Docker, Kubernetes, Terraform, Pulumi and/or BicepGenerative AI e.g. prompt engineering, RAG, fine-tuning, tooling ecosystem Compensation & Benefits Competitive early-stage startup compensation (based on capabilities, experience, and location)Bonus eligibilityHealth insurance with meaningful coverage for dependentsFlexible paid time offEquityFully remote culture with a cluster of teammates in SeattleTraining and learning opportunitiesBe part of a fast-growing, profitable, mission-driven company with industry leading clients tackling the massive opportunity of AI transformation in critical industries Logistics Remote but only USA/CanadaMust be willing to travel to Seattle area for final interview and travel 2x/year for company summitsApplicants must be currently authorized to work in the United States on a full-time basis. We are unable to sponsor or take over sponsorship of employment visas at this time. Next steps If this job sounds great, we’d love to hear from you. If you feel aligned to the company but don’t check all these boxes, we’d still love to hear from you! Compensation Range: $140K - $225K