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Machine Learning Deployment Specialist

vor 2 Monaten


Berlin, Berlin, Deutschland JetBrains Vollzeit
About the Role

We are seeking an experienced Machine Learning Deployment Specialist to join our team at JetBrains AI. In this role, you will play a crucial part in deploying and optimizing ML models, ensuring they run efficiently and effectively in production environments.

Key Responsibilities
  • Model Deployment and Optimization: Optimize and run ML models for inference in high-load production environments.
  • Collaboration and Teamwork: Collaborate with ML engineers to develop scalable and efficient pipelines.
  • Monitoring and Troubleshooting: Monitor and troubleshoot ML models in production, ensuring their reliability and performance.
  • Best Practices and Development: Contribute to the development of best practices for ML deployment and inference.
Requirements
  • Proven Experience: Proven experience in deploying ML models to production, including experience with model optimization techniques (e.g., quantization, knowledge distillation).
  • Programming Skills: Strong programming skills in Python and familiarity with other programming languages (e.g., C++, Java).
  • ML Frameworks and Libraries: Proficiency with ML frameworks such as PyTorch and common libraries for NLP.
  • Cloud Platforms: Experience with cloud platforms like AWS, Google Cloud, or Azure for ML deployment.
  • Containerization and Orchestration: Familiarity with containerization and orchestration tools like Docker and Kubernetes.
Desirable Skills
  • Advanced Knowledge: Advanced knowledge of model serving frameworks such as vLLM, TensorRT-LLM, OpenVINO, or similar.
  • Profiling and Optimization: Experience with profiling ML and MLOps code to identify bottlenecks and achieve better performance.
  • MLOps Tools and Practices: Experience with MLOps tools and practices, including CI/CD for ML.
  • Expertise in Optimization: Expertise in optimizing models for latency and throughput in production environments.
  • NLP and LLMs: Previous work experience with NLP and LLMs.
Technology Stack
  • Git: Git for source control management.
  • Cloud Computing: AWS and GCP for cloud computing infrastructure.
  • ML Development: Python, PyTorch, and Hugging Face as our ML development stack.
  • CI Automation: TeamCity as a CI automation system.