Staff Machine Learning Engineer
Palmetto Clean TechMexico City, Mexico City
Full Time
Posted February 5, 2026
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Job Description
The Senior Machine Learning Engineer will design, build, and maintain Palmetto's MLOps platform, enabling scalable and reliable deployment of machine learning models to support the company's clean energy initiatives. This role involves leading the development of ML infrastructure, mentoring teams, and integrating predictive models into business operations.
Key Responsibilities
- Design, build, and maintain the core MLOps infrastructure and end-to-end ML pipelines.
- Lead the development and implementation of a standardized, scalable ML platform for model deployment and monitoring.
- Collaborate with data teams to integrate ML models into products and operations, ensuring reliable deployment.
- Mentor model developers and promote best practices in model governance, testing, and productionization.
- Monitor deployed models for performance and data drift, implementing automated retraining and alerting mechanisms.
- Create and execute a 2-3 year roadmap for ML capabilities and infrastructure development.
Requirements
- Bachelor's degree in Computer Science, Engineering, or a related quantitative field or equivalent experience.
- 5 years of experience in Machine Learning Engineering, Software Engineering, or Data Science with a dedicated focus on building and scaling ML systems.
- Deep expertise in Python and proficiency in SQL, Docker, CI/CD, and Infrastructure as Code.
- Extensive, hands-on experience architecting systems that use MLOps frameworks such as Kubeflow, MLflow, or Airflow.
- Experience working with public cloud platforms, with GCP preferred.
- Familiarity with statistical modeling toolkits such as PyTorch, XGBoost, TensorFlow, or VertexAI.
- Proven experience in end-to-end problem formulation, including stakeholder requirement gathering, model iteration, and production deployment.
- Strong written and spoken communication skills, with the ability to effectively articulate complex technical concepts to both technical and non-technical audiences.
Benefits & Perks
compensation/salary range not specified
work schedule not specified
work environment perks including unlimited PTO, medical, dental, and vision coverage, paid parental leave, retirement plans
comprehensive benefits package
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