Staff Machine Learning Operations Engineer (AI)

TL;DR

Staff Machine Learning Operations Engineer (AI/MLOps): Spearheading the development and maintenance of machine-learning infrastructure and processes with an accent on scalability, reliability, and efficiency. Focus on automating end-to-end pipelines for data ingestion, model deployment, and establishing robust CI/CD for ML.

Location: Remote (Brazil)

Salary: from $7,500 USD

Company

hirify.global provides software solutions to help home service professionals streamline their operations, scheduling, and payments.

What you will do

• Lead the design, implementation, and maintenance of infrastructure for deploying and monitoring ML models in production.
• Automate end-to-end pipelines for data ingestion, preprocessing, feature engineering, and model deployment.
• Collaborate with data scientists to optimize model performance for production environments.
• Establish CI/CD pipelines to streamline deployment and ensure reproducibility.
• Design monitoring and alerting systems to proactively identify and address model health issues.
• Provide technical leadership and mentorship to junior team members to drive innovation.

Requirements

• Must be based in Brazil
• Updated resume must be submitted in English
• 6+ years of experience in MLOps, data engineering, and/or DevOps roles.
• Proficiency in Python (primary), Java, Scala, or Ruby.
• Extensive experience with cloud platforms (AWS, Azure, or GCP).
• Strong understanding of Docker and Kubernetes, and experience with IaC tools like Terraform or Terragrunt.

Nice to have

• Experience working with Large Language Models (LLMs) and LangChain.
• Solid background in designing data pipelines using Apache Airflow.

Culture & Benefits

• Remote-first environment with a "work in your own time zone" policy.
• Flexible time off for personal travel and experiences.
• Hardware allowance: Newest MacBook/PC plus a $500 home office setup fee.
• Culture of innovation and a defined career path with direct impact on technical decisions.
• Global team with a strong emphasis on work-life balance.