MLOps Engineer (Contractor, part-time)
PAY ATTENTION: only those candidates who meet the listed requirements will receive an answer!
Location
Ukraine
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
Yuliana Malets
Recruiter