Senior machine learning engineer (remote – mexico/argentina)
we are seeking a senior machine learning engineer to work with both open-source and third-party llms to create scalable, production-ready solutions on aws infrastructure.
Key responsibilities
design and implement agentic systems for automated document processing
deploy and manage open-source llms on aws infrastructure
integrate third-party llm apis for entity extraction workflows
build scalable ml pipelines using aws services (ec2, lambda, s3)
optimize model performance and cost efficiency
implement robust data processing and storage solutions
monitor and maintain production ml systems
troubleshoot and resolve production pipeline issues
implement monitoring, alerting, and observability for ml pipelines
build agentic workflows
required technical skills
python – advanced proficiency for ml development and automation
aws ec2 auto scaling groups – managing scalable compute resources
aws s3 – large-scale data storage and retrieval
aws lambda – serverless function deployment and orchestration
aws iam – security policies and access management
machine learning – experience with llms, nlp, and entity extraction
aws agent core – experience building and deploying agent-based systems
production monitoring – cloudwatch, logging, metrics, and alerting systems
troubleshooting – debugging production ml pipelines and resolving performance issues
preferred qualifications
experience with document processing and ocr technologies
familiarity with mlops practices and ci/cd pipelines
experience with containerization (docker) and orchestration
production support experience
what you'll work on
historical document digitization and analysis projects
multi-modal ai systems combining text and image processing
scalable entity extraction pipelines processing thousands of documents
integration of multiple llm providers for optimal accuracy and cost
real-time and batch processing workflows
production monitoring dashboards and alerting systems
impact
work will involve unlocking valuable insights from historical archives, making previously inaccessible information searchable and analyzable for researchers, historians, and institutions worldwide.
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