[Hiring] Python + MLOps Engineer @BairesDev

Role Description

In this role, you'll take machine learning and computer vision models and operationalize them into stable production environments, ensuring they run reliably at scale. Managing mature CI/CD pipelines and cloud environments while enforcing backend code reliability, you'll work within two-week Agile sprints alongside modern AI developer tools. This is your opportunity to bridge the gap between experimental ML work and production-grade systems, where your MLOps expertise directly determines whether models deliver value in the real world.

What You'll Do

• Operationalize machine learning and computer vision models into stable production environments.
• Manage and maintain mature CI/CD pipelines.
• Configure and support dev, stage, and production cloud environments.
• Review pull requests and enforce backend code reliability standards.
• Leverage AI developer tools within Agile sprint cycles to accelerate delivery.

Qualifications

• 8+ years of experience in software engineering.
• Strong proficiency in Python.
• Hands-on experience with MLOps and production model deployment.
• Experience with production CI/CD pipelines.
• Background working in GCP or AWS cloud environments.
• Experience with production model monitoring and performance tracking.
• Advanced proficiency in English.

Requirements

• Experience with agentic workflows and AI coding assistants such as Claude Enterprise.
• Familiarity with automated code review tools such as CodeRabbit AI.
• Experience with AWS cloud migration.

Benefits

• 100% remote work (from anywhere).
• Excellent compensation in USD or your local currency if preferred.
• Hardware and software setup for you to work from home.
• Flexible hours: create your own schedule.
• Paid parental leaves, vacations, and national holidays.
• Innovative and multicultural work environment: collaborate and learn from the global Top 1% of talent.
• Supportive environment with mentorship, promotions, skill development, and diverse growth opportunities.