Design, build, and optimize data workflows for Machine Learning and GenAI solutions in cloud environments.
Develop and deploy Machine Learning and Generative AI (GenAI) models using Azure Machine Learning (AML).
Create and manage data and model pipelines to improve the efficiency of AI and machine learning systems.
Prepare and structure data for advanced AI and GenAI solutions.
Ensure seamless integration of data and AI solutions within cloud architectures, including data security and governance aspects.
Document and rigorously test models and workflows to meet accuracy and performance requirements.
Monitor and enhance the performance of Machine Learning models and services in production.
Manage Data Lake architectures, tailoring data to the needs of Machine Learning and GenAI workloads.
Requirements
Proven experience as a Machine Learning Engineer or in Data Science roles, with strong skills in data pipelines and Machine Learning model development.
Experience working in cloud environments (Azure) for at least 2 years.
Solid proficiency in Python and machine learning libraries such as TensorFlow, PyTorch, or similar.
Advanced English level.
Experience using Azure AI Foundry, Azure ML studio and other Azure data services: Fabric, Synapse, purview.
Experience with Generative AI models and deploying them in production.
Proficiency in DevOps tools (Git, pipelines) and infrastructure as code (Terraform, CloudFormation).
Ability to work in Agile teams under Scrum methodology.
Benefits
Swiss Medical: SMG-30 (family members included).
AWS certifications.
99% discount in Mercado Pago payments.
Internet and connectivity.
Competitive salary and benefits.
English in company.
Ability to work remotely.
An awesome learning environment for you to develop.
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard skills
Machine LearningGenerative AIdata pipelinesPythonTensorFlowPyTorchDevOpsinfrastructure as codeAgileScrum