---
title: "ML Infrastructure Engineer"
company: "Clera"
company_url: "https://www.remjobs.works/companies/clera"
url: "https://www.remjobs.works/job/clera-ml-infrastructure-engineer-01217c17-b9ed-4a89-82e8-5531c7209a44"
apply_url: "https://jobs.ashbyhq.com/clera/8d537344-f8f4-449b-8996-86f8212e59e3"
workplace: onsite
location: "San Mateo"
employment_type: full-time
seniority: mid
role: ai-machine-learning
region: united-states
skills: ["aws", "azure", "cpp", "docker", "gcp", "java", "kubernetes", "python", "rust", "tensorflow"]
date_posted: 2026-09-15T17:22:46.498Z
first_seen_by_remjobs: 2026-09-15T17:50:31.424Z
---

# ML Infrastructure Engineer

**Clera** · San Mateo

Apply: https://jobs.ashbyhq.com/clera/8d537344-f8f4-449b-8996-86f8212e59e3

## About Clera

Stop applying to startups. Start getting introduced. Clera connects you directly with hiring managers at the companies you want to work for.

## About the role

##### About the Role

This is a hands-on infrastructure engineering role at an early-stage enterprise AI company building a context and data governance layer for AI agents deployed in highly regulated industries. You will own the inference and model-serving infrastructure end to end, making production AI agents fast, reliable, and scalable as concurrency grows.

##### What You'll Do

- Design, build, and own inference and model-serving infrastructure from initial architecture through production deployment.

- Scale systems that enable AI agents to run reliably and efficiently under increasing concurrent load.

- Identify and resolve infrastructure bottlenecks in collaboration with ML and platform engineering teams.

- Drive performance optimization across latency, throughput, and reliability for production workloads.

##### What We're Looking For

- 5+ years building and operating ML inference systems, model-serving platforms, or ML infrastructure in production environments.

- Hands-on experience designing and scaling inference-serving systems using frameworks such as TensorFlow Serving, TorchServe, Triton, KServe, or equivalent custom solutions.

- Strong distributed systems fundamentals, including experience managing concurrent requests and resource allocation under load.

- Proficiency with containerization and orchestration technologies, particularly Docker and Kubernetes, for ML workloads.

- Experience with cloud infrastructure platforms (AWS, GCP, or Azure) for deploying and managing ML systems.

- Solid monitoring and observability skills using tools such as Prometheus, Grafana, ELK, or distributed tracing solutions.

- Proficiency in at least one systems or backend language: Python, Go, Rust, C++, or Java.

- Familiarity with knowledge graphs, semantic search, or graph databases is a plus.

- Background in agentic or autonomous AI systems, real-time inference, or enterprise data infrastructure is a plus.

##### Location

On-site in San Mateo, California, United States. Visa sponsorship is not available for this role.

---

Source: Clera's own career page, read by RemJobs. Canonical HTML version: https://www.remjobs.works/job/clera-ml-infrastructure-engineer-01217c17-b9ed-4a89-82e8-5531c7209a44