MLOps Engineer (AI)

TL;DR

MLOps Engineer (AI): Building and implementing end-to-end machine learning features and robust MLOps practices with an accent on production readiness, system reliability, and data/ML pipeline development. Focus on establishing comprehensive testing processes, deploying models at scale, and optimizing revenue strategies through AI-driven insights.

Location: Hybrid with expected travel into Paddington, UK 2 days per week.

Company

hirify.global is a product company that builds an intelligently designed platform transforming the hospitality industry across 150 countries.

What you will do

• Develop and implement end-to-end machine learning features with a strong emphasis on production readiness and system reliability.
• Establish and maintain robust MLOps practices, including CI/CD for model training, testing, deployment, and monitoring.
• Design, build, and maintain highly reliable data and ML pipelines to structure large datasets.
• Implement comprehensive software quality and testing processes for ML systems, including unit, integration, and end-to-end testing.
• Design, train, and test machine learning models where needed to improve pricing optimization.
• Implement model performance monitoring and collaborate cross-functionally to improve system performance, stability, and usability.

Requirements

• Bachelor's degree in Computer Science, Statistics, Mathematics, Data Science, or a related quantitative field.
• 3+ years of experience in a data engineering or machine learning role, with demonstrated success in MLOps and deploying models to production.
• Proven expertise in designing and implementing ML testing strategies (e.g., data validation, model correctness).
• Expertise in deploying ML models at scale on AWS, with experience using MLFlow or similar platforms.
• Strong Python programming skills and adherence to software engineering best practices.
• Expert-level SQL skills and experience working with large datasets.
• Excellent communication and collaboration skills for cross-functional teamwork.

Nice to have

• Experience with CI/CD tooling (e.g., GitHub Actions, Jenkins) specifically for ML pipelines and Airflow DAG deployment.
• Experience with data quality monitoring tools and frameworks.
• Master’s or PhD in Computer Science, Data Science, or a related field.

Culture & Benefits

• Remote-First company with flexible PTO in accordance with local labor requirements.
• Monthly Wellness Fridays for an extra-long weekend every month.
• Full Paid Parental Leave.
• Home office stipend based on country of residency.
• Access to professional development courses in hirify.global University.
• Diverse team of 650+ employees across 40+ countries.