Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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Зарплата и рынок
Мало
$221к-260к/год
$200к$240кмедиана$270к
По похожим ролям (48) ~ $240к/год
На СНГ рынке: $4.6к/мес ($4к - $4.7к)
92
Крутая вакансия
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Влиятельная роль в трендовом домене AI-медицины с передовым стеком технологий и прозрачными, щедрыми бенефитами.
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Достойная оплатаПередовой стекТрендовый доменОтличные бонусыЧеткие задачи
Оценка от Hirify AI
Мэтч & Сопровод
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
ML Infrastructure Engineer (AI): Building and optimizing scalable inference infrastructure for machine learning models with an accent on Kubernetes orchestration, model serving, GPU utilization, and low-latency performance. Focus on designing distributed systems, developing model API orchestration, and scaling compute-heavy AI workloads across research and product engineering.
Location: Hybrid, SF Office; compensation and benefits are structured for U.S. geographic markets.
Salary: $221K–$260K base pay, with compensation varying by U.S. market and job-related experience.
Company
hirify.global develops an AI-powered healthcare platform that converts patient-clinician conversations into structured clinical notes and integrates with electronic medical records.
What you will do
Design, deploy, and maintain scalable Kubernetes clusters for AI model inference and training.
Develop and optimize model-serving infrastructure for high performance and low latency.
Scale backend infrastructure for AI products, including model deployment, throughput, and compute efficiency.
Optimize compute-heavy workflows and GPU utilization for machine learning workloads.
Build a robust model API orchestration system.
Define infrastructure scaling strategies with leadership as the company grows.
Requirements
5+ years of experience building and deploying machine learning models in production.
Deep understanding of container orchestration and distributed systems architecture.
Expertise in Kubernetes administration, including custom resource definitions, operators, and cluster management.
Experience developing APIs and managing distributed systems for batch and real-time workloads.
Excellent communication skills for collaboration across research and product engineering.
Nice to have
Experience with NVIDIA Triton Server, vLLM, TRT-LLM, PyTorch, TensorFlow, or distributed training and inference libraries.
Familiarity with GPU cluster management and CUDA optimization.
Knowledge of Terraform, Ansible, GitOps, container registries, image optimization, and multi-stage builds.
Experience orchestrating ASR or LLM models for generative AI applications.
Culture & Benefits
Flexible work hours and an inclusive, supportive environment focused on empathy for clinicians and patients.
Paid holidays, flexible PTO for salaried employees, and paid parental leave.
Medical, dental, and vision coverage, HSA contributions, FSA access, and commuter benefits.
401(k) matching, personal device allowance, lifestyle wallet, and mental health support.
Paid sabbatical after five years and equity grants for full-time employees.
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