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Nvidia Senior Applied Machine Learning Engineer NEMO Microservices 
United States, Texas 
175331898

12.08.2024

What you'll be doing:

  • Development of new generation of Compound AI Systems platform with reasoning capabilities that supports working across multiple modalities including but not limited to images, videos, audio, and text.

  • Development of distributed cloud applications, microservices and MLOps platforms able to scale up to huge models

  • Creating microservices for task-specific AI cloud services

  • Implementing core infrastructure for cloud-native AI training and inference

  • Relentlessly pursue speed of light performance under high load

What we need to see:

  • BS, Masters, or equivalent experience in computer science, computer architecture, or related field

  • 5+ years of experience

  • Exceptional coding skills, striving for creating high-quality software

  • Ability to work independently, define project goals and scope, interact directly with open-source community, and manage your own development effort

  • Experience implementing microservices and cloud-native applications using HTTP REST, gRPC, protobuf, JSON and related technologies

  • Experience deploying application on Kubernetes platform, familiarity with helm charts, kustomize, k8s operator.

  • Understanding of performance, security, and reliability in complex distributed infrastructure

  • Excellent Python or Golang programming and software design skills, including debugging, performance and service health analysis, and test design.

Ways to stand out from the crowd:

  • Experience deploying machine learning or statistical models into production environments, especially experience with frameworks such as PyTorch, Tensorflow, ONNX Runtime, and TensorRT

  • Background with deep learning frameworks such as Megatron Core, NeMo, HuggingFace Accelerate, HuggingFace Transformers, DeepSpeed, and similar

  • Experience with MLOps orchestration platforms such as Seldon Core, Kserve, BentoML and similar

  • Experience with inference engines such as VLLM, TensorRT-LLM and similar

  • Knowledge of or experience with developing production NLP systems as well as experience working with high availability environments

You will also be eligible for equity and .