Glocomms
Role Overview
We're seeking a hands-on
AI/ML Engineer
with a passion for solving real-world problems using cutting-edge technologies. This role focuses on building and deploying solutions using large language models (LLMs), traditional machine learning techniques, and data-centric workflows. You'll work closely with cross-functional teams to design, test, and scale AI tools that deliver measurable business value. Ideal candidates will bring curiosity, clarity, and creativity to their work-whether they've built prototypes with tools like ChatGPT, cleaned messy datasets using Python, or explained complex AI concepts in simple terms to non-technical colleagues. Key Responsibilities AI Solution Design & Development Design and iterate prompt structures and workflows using LLMs and other AI tools. Build ML models using techniques like XGBoost, decision trees, and regression models. Collaborate with business and technical stakeholders to refine AI behavior. Analyze model performance, resolve edge cases, and enhance output reliability. Document model assumptions, risks, and behaviors in a transparent, testable format.
Data Preparation & Integration Extract and prepare structured and unstructured data (e.g., PDFs, CAD metadata). Clean, transform, and validate datasets to optimize model performance. Integrate AI outputs into existing tools and workflows.
Deployment & Testing Package and test models using Python, Docker, Conda, and Jupyter. Support deployment into cloud environments and user-facing applications.
Qualifications Minimum Requirements Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experience). Strong Python skills and experience with LLMs or generative AI. Familiarity with ML techniques such as XGBoost, decision trees, or regression. Experience with data cleaning, parsing, and transformation. Comfortable working in cross-functional teams.
Preferred Qualifications Hands-on experience with LLMs (e.g., OpenAI, Anthropic, Hugging Face). Experience in manufacturing or engineering-adjacent environments. Exposure to cloud platforms (e.g., AWS, Azure) and API integration. A curious mindset and a track record of iterating quickly on real-world use cases. Ability to clearly explain AI concepts to non-technical audiences.
What We Value
We're especially interested in candidates who ***** Share examples of AI or automation projects they've built or tested. Demonstrate how they've applied ML in production or pilot settings. Show enthusiasm for solving problems and learning from feedback.
We're seeking a hands-on
AI/ML Engineer
with a passion for solving real-world problems using cutting-edge technologies. This role focuses on building and deploying solutions using large language models (LLMs), traditional machine learning techniques, and data-centric workflows. You'll work closely with cross-functional teams to design, test, and scale AI tools that deliver measurable business value. Ideal candidates will bring curiosity, clarity, and creativity to their work-whether they've built prototypes with tools like ChatGPT, cleaned messy datasets using Python, or explained complex AI concepts in simple terms to non-technical colleagues. Key Responsibilities AI Solution Design & Development Design and iterate prompt structures and workflows using LLMs and other AI tools. Build ML models using techniques like XGBoost, decision trees, and regression models. Collaborate with business and technical stakeholders to refine AI behavior. Analyze model performance, resolve edge cases, and enhance output reliability. Document model assumptions, risks, and behaviors in a transparent, testable format.
Data Preparation & Integration Extract and prepare structured and unstructured data (e.g., PDFs, CAD metadata). Clean, transform, and validate datasets to optimize model performance. Integrate AI outputs into existing tools and workflows.
Deployment & Testing Package and test models using Python, Docker, Conda, and Jupyter. Support deployment into cloud environments and user-facing applications.
Qualifications Minimum Requirements Bachelor's degree in Computer Science, Engineering, or related field (or equivalent experience). Strong Python skills and experience with LLMs or generative AI. Familiarity with ML techniques such as XGBoost, decision trees, or regression. Experience with data cleaning, parsing, and transformation. Comfortable working in cross-functional teams.
Preferred Qualifications Hands-on experience with LLMs (e.g., OpenAI, Anthropic, Hugging Face). Experience in manufacturing or engineering-adjacent environments. Exposure to cloud platforms (e.g., AWS, Azure) and API integration. A curious mindset and a track record of iterating quickly on real-world use cases. Ability to clearly explain AI concepts to non-technical audiences.
What We Value
We're especially interested in candidates who ***** Share examples of AI or automation projects they've built or tested. Demonstrate how they've applied ML in production or pilot settings. Show enthusiasm for solving problems and learning from feedback.