Вакансия MLOps Engineer

Skills

• Git
• LLM
• Python
• AWS SageMaker
• Vertex AI
• Azure ML Studio
• AWS
• Azure
• GCP
• Kubernetes
• RAG
• API

Описание вакансии

Necessary skills and qualifications

• At least 4 years of experience deploying and managing ML models with a strong understanding of AI/ML lifecycle management, automation tools, and version control systems (e.g., Git)
• Experience with deploying open-source Large Language Models (LLMs)
• Proficiency with ML Ops for assessing and monitoring model performance and scalability
• Familiarity with Python, and experience with MLOps frameworks/tools (e.g. Sagemaker pipelines/ Azure ML Studio/ VertexAI)
• Expertise in deploying models on cloud platforms such as AWS, Azure, or GCP
• Good knowledge of machine learning and deep learning principles
• Strong communication and collaboration skills, with the ability to work effectively in cross-functional teams
• Upper-intermediate level of English proficiency

Will be a plus

• Experience with Kubernetes
• Familiarity with Retrieval-Augmented Generation (RAG) pipelines
• Knowledge and experience in API development

Responsibilities

• Develop, refine, and use ML engineering platforms and components, development workflow pipelines
• Deployment of open-source LLMs and other models to different instances
• Collaborate closely with client-facing teams to understand their needs and provide technical support
• Rapid model deployment implementation
• Developing process-related documentation
• Kubeflow and MLFlow upgrade