Senior AI/ML Engineer (On-Premise + Tabular Data)

Resumen

• $970.000
• Contractor / Freelance
• Publicado el 7 may 2026 a las 20:05, hace 1 mes
• Remoto

Descripcion del puesto

Únete a nuestra red de talento y conéctate con clientes de EE.UU. para proyectos flexibles basados en desarrollo. 5+ años de experiencia profesional en ingeniería de IA/ML. Inglés avanzado requerido. Título universitario de cuatro años completado. Experiencia comprobada construyendo y validando modelos de aprendizaje supervisado en grandes conjuntos de datos tabulares. Requisitos: - 5+ years of professional AI/ML engineering experience - Advanced English is required - Successful completion of a four-year college degree is required - Proven experience building and validating supervised learning models on large-scale tabular datasets - Demonstrated experience extracting predictive signals and performing feature engineering on raw transactional data - Track record of designing rigorous back-testing frameworks to verify model accuracy against historical project outcomes - Hands-on experience profiling, cleaning, and normalizing messy enterprise data within PostgreSQL environments - Solid background in deploying containerized models (Docker/ONNX) within on-premise or air-gapped infrastructures - Expertise in ensemble methods such as XGBoost, LightGBM, and CatBoost for high-stakes regression tasks - Adept at balancing CPU vs. GPU inference tradeoffs to optimize performance in private cloud environments - Well-versed in the architectural constraints of building AI systems without reliance on cloud-native services - Skilled at translating complex model outputs into actionable ROI and cost-estimation insights - Ability to work through new and difficult issues and contribute to libraries as needed - Ability to create and maintain continuous integration and delivery of applications - Forensic attention to detail - A positive mindset and a can-do attitude - Experience working on Agile / Scrum teams - Meaningful experience working on large, complex systems

Requisitos principales

• 5+ years of professional AI/ML engineering experience
• Advanced English is required
• Successful completion of a four-year college degree is required
• Proven experience building and validating supervised learning models on large-scale tabular datasets
• Demonstrated experience extracting predictive signals and performing feature engineering on raw transactional data
• Track record of designing rigorous back-testing frameworks to verify model accuracy against historical project outcomes
• Hands-on experience profiling, cleaning, and normalizing messy enterprise data within PostgreSQL environments
• Solid background in deploying containerized models (Docker/ONNX) within on-premise or air-gapped infrastructures
• Expertise in ensemble methods such as XGBoost, LightGBM, and CatBoost for high-stakes regression tasks
• Adept at balancing CPU vs. GPU inference tradeoffs to optimize performance in private cloud environments
• Well-versed in the architectural constraints of building AI systems without reliance on cloud-native services
• Skilled at translating complex model outputs into actionable ROI and cost-estimation insights
• Ability to work through new and difficult issues and contribute to libraries as needed
• Ability to create and maintain continuous integration and delivery of applications
• Forensic attention to detail
• A positive mindset and a can-do attitude
• Experience working on Agile / Scrum teams
• Meaningful experience working on large, complex systems