Manager, Machine Learning Operations (AI)

Location: hirify.global Corporate Offices (0900)

Company

hirify.global operates a retail and e-commerce business supported by data science and machine learning capabilities.

What you will do

• Lead, manage, coach, develop, and assess ML Ops engineers.
• Guide implementation of the full machine learning lifecycle, including ETL pipelines, model deployment, and cloud infrastructure.
• Own the roadmap for Machine Learning Engineering and Data Science tools, reusable frameworks, and standardized solutions.
• Research and prototype machine learning infrastructure while providing technical guidance to Data Science leaders.
• Develop monitoring, alerting, automated testing, and infrastructure practices that improve reliability and performance.
• Document implementations and communicate best practices across the broader data organization.

Requirements

• Bachelor’s degree in Data Science, Computer Science, Statistics, Applied Mathematics, or an equivalent quantitative field.
• 5+ years of Machine Learning Engineering experience with independent project delivery and 2+ years of managerial or leadership experience.
• Production ML Ops expertise with Docker, Kubernetes, CI/CD, Git, API development, model serving, and automated testing.
• Experience deploying, scaling, and operationalizing machine learning models with Data Scientists.
• Knowledge of Google Cloud Platform, especially Vertex AI, BigQuery, and Dataproc, as well as distributed computing and big data technologies.
• Advanced Python and machine learning library expertise, including TensorFlow, PyTorch, or scikit-learn, plus Agile development experience.

Nice to have

• Master’s degree and 7+ years of Machine Learning experience.
• Proficiency in Java or other programming languages.
• Retail or e-commerce experience.
• Experience with optimization techniques, Gurobi, linear programming, or mixed-integer programming.
• Experience with agentic AI systems, autonomous workflows, or LLM-driven agents.

Culture & Benefits

• Continuous learning and development through coaching, pair programming, and code review.
• Agile environment focused on iterative development and continuous delivery.
• Fast-paced environment requiring collaboration, prioritization, and regular attendance.
• Reasonable accommodations may be available for individuals with disabilities.