5 дней назад
ML Infrastructure Engineer (AI)
14 167 - 25 000$
Вакансия из Hirify Global, списка международных tech-компанийДля мэтча и отклика нужен Plus
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
ML Infrastructure Engineer (AI): Building and operating the production platform for ML models used in autonomous factories with an accent on model deployment, serving, and reliability. Focus on standardizing deployment patterns using MLflow, Dagster, and EKS, and ensuring high availability and low latency for diverse ML workloads.
Location: On-site in Los Angeles, CA. Must be a U.S. citizen, lawful permanent resident, or eligible for ITAR authorizations.
Salary: $170,000 – $300,000
Company
is building autonomous factories to reindustrialize America by combining AI, robotics, and full-stack manufacturing for the aerospace and defense industries.
What you will do
- Build the production platform enabling factories to safely depend on models for drawing extraction, forecasting, and scheduling.
- Develop shared batch and online serving for tabular, vision, and document-AI workloads with clear SLAs.
- Create repeatable release and evaluation processes, including canaries, shadow deployments, and A/B tests.
- Own online feature serving and implement mechanisms to detect training-serving skew and model degradation.
- Develop operational tooling for telemetry, incident response, GPU management, and secure model routing.
- Create APIs, SDKs, and documentation for seamless adoption by other engineering teams.
Requirements
- Track record of building and operating production ML infrastructure across multiple workloads.
- Strong production-level Python and SQL skills (typing, testing, API design).
- Hands-on experience with Kubernetes, containers, and distributed-system failure modes.
- Engineering background with model registries, feature systems, and model CI/CD workflows.
- Practical judgment regarding latency, throughput, availability, and infrastructure cost.
- Must be a U.S. citizen, lawful permanent resident, or eligible for ITAR authorizations.
Nice to have
- Experience implementing feature stores like Feast or Tecton.
- Production work with Ray Serve, KServe, Triton, BentoML, or SageMaker.
- Experience serving and evaluating generative pipelines or vision/document-understanding models.
- Expertise in GPU inference optimization or performance-sensitive AI services in Go/Rust.
- Contributions to open-source ML infrastructure projects (MLflow, KServe, Ray).
Culture & Benefits
- Comprehensive medical, dental, vision, and life insurance plans.
- 401(k) retirement plan.
- Flexible vacation policy and equity.
- Relocation support may be provided based on business needs.
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