обновлено 12 часов назад
AI Platform Engineer
130 000 - 180 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
AI Platform Engineer (LLM Serving/Cloud Infrastructure): Building and operating enterprise-scale AI inference and model-serving platforms with an accent on distributed systems, Kubernetes, GPU optimization, and cloud-native infrastructure. Focus on optimizing inference latency and throughput, designing autoscaling and request routing, implementing MLOps lifecycle management, and ensuring observability, security, and high availability.
Location: 100% remote within the Continental United States
Salary: $130,000–$180,000 annually, based on experience.
Company
is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States.
What you will do
- Design, build, and maintain scalable AI inference and model-serving platforms for production environments.
- Architect highly available cloud-native infrastructure for LLMs, foundation models, and machine learning services.
- Optimize inference latency, throughput, GPU utilization, memory management, workload orchestration, and request routing.
- Implement model deployment, versioning, rollback, lifecycle management, monitoring, logging, tracing, and alerting.
- Build caching, API gateway, authentication, authorization, security, and high-availability solutions.
- Collaborate with AI researchers, ML engineers, DevOps teams, and software engineers while mentoring engineers and driving infrastructure optimization.
Requirements
- Must be based in the Continental United States.
- 10+ years of professional experience in distributed systems, infrastructure, cloud platforms, or machine learning platform engineering.
- Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Artificial Intelligence, or a related technical discipline.
- Strong Python skills and proficiency in Go, Rust, or C++.
- Experience with LLM serving, model inference optimization, vLLM, TensorRT-LLM, Triton Inference Server, Ray Serve, or similar frameworks.
- Expertise in Kubernetes, Docker, cloud platforms, CUDA, NVIDIA GPUs, distributed systems, networking, observability, and security.
Nice to have
- Experience with multi-region AI platforms and globally distributed inference services.
- Knowledge of quantization, pruning, compression, speculative decoding, KV cache optimization, and mixed-precision inference.
- Experience with MLOps, GitOps, Terraform, Bicep, CloudFormation, and CI/CD automation.
- Familiarity with Istio, Linkerd, API gateways, event-driven architectures, FinOps, and enterprise AI governance.
- Open-source contributions, technical publications, patents, conference presentations, or experience supporting large-scale AI APIs.
Culture & Benefits
- Full-time direct W2 employment.
- Career growth within an established technology consulting and software development organization.
- Work remotely within the Continental United States.
- U.S. citizens, Green Card holders, EAD holders, and H-1B transfer candidates are eligible to apply.
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