Senior Machine Learning Engineer (Generative AI)

TL;DR

Senior Machine Learning Engineer (Generative AI): Leading the end-to-end development and lifecycle management of machine learning models powered by proprietary data with an accent on building scalable, production-grade ML systems. Focus on designing model pipelines, deploying scalable APIs, and troubleshooting model drift and performance bottlenecks in production.

Location: Remote, Colombia

Company

hirify.global is a premier partner for global enterprises, specializing in digitization, automation, and the development of next-generation digital products and services.

What you will do

• Design, build, and deploy end-to-end machine learning models using proprietary datasets.
• Own the full ML lifecycle, including data preparation, feature engineering, model training, and validation.
• Package and expose trained models as scalable APIs for consumption by AI Engineers and downstream systems.
• Build and maintain model pipelines for versioning, retraining, and continuous improvement workflows.
• Monitor production model performance to ensure accuracy, reliability, and relevance over time.
• Collaborate with Data Scientists and Principal AI Engineers to align models with system architecture.

Requirements

• Strong experience in machine learning engineering with a proven track record of production deployment.
• Proficiency in Python and ML frameworks such as TensorFlow, PyTorch, and scikit-learn.
• Hands-on experience deploying ML models as APIs or microservices.
• Familiarity with MLOps practices, including model versioning and monitoring.
• Strong software engineering fundamentals regarding testing, scalability, and performance optimization.
• Must be based in Colombia.

Nice to have

• Experience with cloud platforms (AWS, GCP, or Azure) and services like SageMaker or Vertex AI.
• Familiarity with containerization and orchestration tools such as Docker and Kubernetes.
• Experience with real-time or low-latency ML systems.
• Exposure to LLMs or hybrid AI/ML systems.
• Experience building data pipelines using Airflow or Spark.

Culture & Benefits

• Commitment to equal opportunity employment and accessibility.
• Opportunity to work at the core of an AI ecosystem building impactful product features.
• Collaborative environment partnering with global enterprises across North and South America.