Site Reliablity Engineer

About the Role

Trimble is seeking an enthusiastic AI/ML Engineer (P1) to join our Construction Management Solutions (CMS) team. This role offers an exceptional opportunity to accelerate your career in AI/ML engineering, working directly alongside seasoned data scientists and principal engineers to transform complex real-world data into actionable, production-grade enterprise tools.

Key Responsibilities

• Assist in developing, implementing, and fine-tuning machine learning algorithms and foundational models, with direct exposure to advanced deep learning paradigms.
• Own data collection, sanitization, exploratory analysis, and feature engineering tasks to ensure data quality, consistency, and industry-specific relevance.
• Execute routine testing, debugging, and comprehensive documentation of ML codebases and pipelines to ensure reproducible, high-performance systems.
• Support the integration of trained models into enterprise-grade applications, adhering to standard architectural patterns while learning essential MLOps practices such as containerization, artifact tracking, and performance monitoring.
• Partner with senior engineers and domain specialists to translate ambiguous business requirements into well-defined machine learning tasks and actionable delivery milestones.

Requirements & Tech Stack

• Python programming proficiency, with practical experience manipulating datasets and building algorithms using standard data science libraries including NumPy, pandas, and scikit-learn.
• Strong conceptual grounding in machine learning theory, evaluation metrics, statistical techniques, and foundational deep learning concepts.
• Solid grasp of fundamental data structures, basic data modeling principles, and software engineering practices.
• Proven ability to follow structured engineering methodologies to troubleshoot issues of defined scope and arrive at clear, practical solutions.
• Familiarity with version control systems (Git) for collaborative branch-based development.
• Comfort with basic Linux CLI and Bash scripting.

Bonus Points

• Hands-on familiarity with modern deep learning toolkits such as PyTorch or TensorFlow.
• Basic foundational understanding of cloud environments (AWS, Microsoft Azure, or GCP) and their AI/ML service offerings.
• Early evidence of production-oriented ML work demonstrated through capstone projects, research publications, or active GitHub repositories.
• Academic exposure to, or experimentation with, Generative AI models, transformer architectures, and Large Language Models (LLMs).

Qualifications

• Bachelor's degree in Computer Science, Mathematics, Engineering, Statistics, or a closely related quantitative field.
• Trimble's Professional ladder typically requires four or more years of formal education.