9 месяцев назад
Senior/Staff Machine Learning Systems Engineer (AI)
179 000 - 248 000$
Мэтч & Сопровод
Для мэтча с этой вакансией нужен Plus
Описание вакансии
Текст:
TL;DR
Senior/Staff Machine Learning Systems Engineer (AI): Building and optimizing the core infrastructure that powers machine learning models with an accent on enhancing the scalability, efficiency, and performance of AI-driven solutions. Focus on model deployment, throughput optimization, and compute efficiency.
Location: San Francisco-Hybrid
Salary: $179K – $248K
Company
is an AI-powered platform purpose-built for medical conversations, improving clinical documentation efficiencies.
What you will do
- Design, deploy, and maintain scalable Kubernetes clusters for AI model inference and training.
- Develop, optimize, and maintain ML model serving and training infrastructure, ensuring high-performance and low-latency.
- Collaborate with ML and product teams to scale backend infrastructure for AI-driven products, focusing on model deployment, throughput optimization, and compute efficiency.
- Optimize compute-heavy workflows and enhance GPU utilization for ML workloads.
- Build a robust model API orchestration system.
Requirements
- Strong experience in building and deploying machine learning models in production environments.
- 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 both batch and real-time workloads.
- Excellent communication skills, with the ability to interface between research and product engineering.
Nice to have
- Expertise with model serving frameworks such as NVIDIA Triton Server, VLLM, TRT-LLM and so on.
- Expertise with ML toolchains such as PyTorch, Tensorflow or distributed training and inference libraries.
- Familiarity with GPU cluster management and CUDA optimization.
- Knowledge of infrastructure as code (Terraform, Ansible) and GitOps practices.
- Experience orchestrating across ASR models or LLM models for building various GenAI applications.
Culture & Benefits
- Comprehensive Health Plans: Medical, Dental, and Vision plans. covers 100% of the premium for you and 75% for dependents.
- Yearly Learning and Development Budget for coaching, courses, workshops, conferences, and more.
- Flexible work hours and an inclusive culture.
- Competitive compensation and equity grants.
- 16 weeks paid parental leave.
- Generous Time Off: 13 paid holidays and flexible PTO.
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