ML/AI Ops Engineer

This is a fully remote position, open to applicants in Costa Rica.

📋 Description

• Take ownership of the comprehensive operationalization of ML and AI solutions—from their development to establishing scalable, reliable production systems that integrate smoothly with other digital tools.

• Design, automate, and sustain CI/CD pipelines for model training, testing, deployment, and retraining (Azure DevOps, Databricks).

• Construct, enhance, and version model lifecycle workflows, ensuring reproducibility, lineage, and governance across the ML/AI platform.

• Oversee production models for performance, drift, reliability, and resource utilization; implement automated retraining workflows.

• Optimize compute, storage, and orchestration across the Databricks platform to guarantee efficient and cost-effective operations.

• Collaborate intimately with ML/AI Scientists, Data Engineers, and the DWH team to convert research-grade models into production-ready services.

• Contribute to the advancement of our ML/AI platform, tooling, automation standards, and best practices.

⛳️ Requirements

• Proven experience in operationalizing ML/AI models, including deployment, automation, monitoring, and lifecycle management.

• Proficient programming skills in Python, PySpark, and SQL with clean, efficient, production-ready code.

• Experienced in feature engineering with a solid understanding of data engineering fundamentals—designing, validating, and optimizing feature pipelines while ensuring feature consistency.

• Experience in building Vector embeddings & RAG systems.

• Familiarity with the development of ML and LLM models and the libraries used.

• Proficient with MLflow (or similar tools) for model tracking, registry management, and lifecycle operations.

• Familiarity with CI/CD pipelines (Azure DevOps preferred).

• Strong understanding of data versioning, model versioning, reproducibility, and data lineage within governed ML/AI environments.

• Experience in designing, consuming, or integrating REST APIs to expose ML/AI models as services and support real-time or near-real-time inference.

• Experience in monitoring production models, identifying drift or performance issues, and implementing corrective workflows.

• A collaborative, systems-thinking mindset that fosters close teamwork with ML/AI Scientists, Data Engineers, and the Data Warehouse team.

🏝️ Benefits

• Two weeks of paid vacation, 12 statutory holidays, plus 4 additional global VeeaMe Days for self-care and 24 paid volunteer hours annually through Veeam Cares.

• Paid parental leave: 8 days for fathers, 122 days for birthing parents, and 92 days for adoptive parents.

• Comprehensive medical, dental, and vision coverage fully funded through INS Premium for employees and their dependents.

• Mental health support, therapy sessions, and virtual care provided via our Employee Assistance Program.

• Retirement and social security contributions through Costa Rica’s statutory programs.

• Life insurance amounting to 24 times the monthly salary, along with disability and funeral coverage.

• Daily cafeteria subsidy.

• Support for fertility, adoption, and surrogacy, plus 24 paid volunteer hours through Veeam Cares.

• Opportunities for learning and growth through on-demand libraries (LinkedIn Learning, O’Reilly), mentoring, workshops, and learning events such as our annual Global Day of Learning.