Remote job
Senior Machine Learning Engineer
Job details
About this role
Role overview
A senior engineering role focused on building and operating production-grade machine learning systems for enterprise clients across Latin America. The position owns the end-to-end ML lifecycle—from data ingestion through monitoring—while partnering with data scientists, engineers, product teams, and business stakeholders. It is fully remote, with candidates based anywhere in LATAM.
Responsibilities
- Design, develop, and deploy scalable machine learning solutions that meet production reliability targets. - Build and optimize end-to-end ML pipelines covering ingestion, feature engineering, training, evaluation, deployment, and monitoring. - Develop distributed data processing workflows using PySpark and SQL for large-scale applications. - Deploy and manage ML models across AWS, Azure, GCP, and Databricks environments. - Apply MLOps practices such as model versioning, experiment tracking, CI/CD, monitoring, and lifecycle management. - Maintain containerized ML workloads on Kubernetes for model serving, batch processing, and orchestration. - Continuously improve model performance, scalability, reliability, and operational efficiency.
Requirements
- Bachelor's or Master's degree in Computer Science, Machine Learning, Data Science, or a related field—or equivalent practical experience. - 5+ years as a Machine Learning Engineer working on production-grade systems. - Strong programming skills in Python, SQL, and PySpark for large-scale data processing. - Hands-on experience with Scikit-learn, PyTorch, TensorFlow, and XGBoost. - Proven track record building ML pipelines with MLflow or comparable MLOps platforms. - Cloud deployment experience across AWS, Azure, GCP, or Databricks. - Familiarity with Kubernetes and containerized ML workloads. - Excellent communication and cross-functional collaboration skills.
Nice to have
- MLOps, CI/CD, and model governance experience. - Knowledge of model monitoring, observability, and performance optimization techniques. - Agile development background. - Familiarity with Docker, workflow orchestration tools, and large-scale distributed computing platforms. - Exposure to generative AI, LLMs, or other advanced ML systems.
Benefits and work setup
- Fully remote position open to candidates across LATAM, with skill-based hiring and a non-discrimination policy.