Machine Learning Architect

TL;DR

Machine Learning Architect (AWS): Designing and delivering ML system solutions for customer projects with an accent on ML system design, MLOps, and production-grade implementation on AWS. Focus on translating customer requirements into architecture and backlog execution, applying DevOps/CI/CD and Infrastructure as Code practices, and troubleshooting ML workloads across dev, test, and production.

Location: Argentina

Company

hirify.global is a cloud native services company helping organizations modernize and build solutions using AWS.

What you will do

• Guide delivery through Agile ceremonies and help translate customer requirements into a workable engineering backlog.
• Lead requirements gathering, backlog grooming, and architecture discussions with stakeholders.
• Delegate and coordinate engineering work to complete customer projects.
• Apply DevOps pipeline practices (build automation, branching strategies, CI/CD, Infrastructure as Code, security, monitoring, logging, alerting).
• Troubleshoot and resolve issues in customer dev, test, and production environments.
• Automate testing across multiple levels and write production-quality code with unit and integration tests.

Requirements

• Experience with Infrastructure as Code tools: CloudFormation, CDK, and/or Terraform.
• Expert experience with Amazon SageMaker and ML libraries such as TensorFlow, MXNet, PyTorch, and Scikit-learn.
• Strong ML fundamentals: feature engineering, hyperparameter tuning, and optimization strategies.
• Familiarity with MLOps tools such as MLflow, Neptune, and Comet.
• Ability to communicate complex technical concepts clearly to non-technical audiences.
• Ability to work with customers to identify gaps in requirements and propose actionable next steps.

Culture & Benefits

• 100% remote work with a worldwide team.
• Generous holidays and flexible PTO.
• Paid exams and certifications, plus professional development support and annual learning stipend.
• Phantom equity and peer bonus awards.
• Equipment and office stipend, plus a state-of-the-art laptop and tools.

Hiring process

• Application screening may use AI/automated tools to match qualifications to job requirements.
• Final hiring decisions are made by trained recruitment professionals.