LLM Infrastructure Engineer
USD 2,500–4,000 / month
Hire Hangar, a company in real estate, construction and proptech, is hiring for the role of LLM Infrastructure Engineer. This is a remote position, and the posting gives Asunción as the location. We classify it under data and machine learning. The posting names LLM, CI/CD, Docker, Kubernetes, AWS and Terraform. English is required. There are 19 open positions from Hire Hangar on this site, 3 of them in IT and engineering.
Posted 3 days ago · Last checked 2026-10-19
About Hire Hangar
Real estate, construction and proptech Non-tech company with an IT team 19 open positions, 16% in IT and engineering. Most open roles: Sales (5), Marketing and communications (4), Finance and legal (2).
Similar jobs
18 open data and machine learning jobs in Argentina · 697 open remote data and machine learning jobs · 175 open remote data and machine learning jobs in EMEA
- Staff ML Accelerator Architect — Waymo, Mountain View, CA, USA; New York, New York, USA
- Data Analyst — Attain Talent, United States - Hybrid
- Senior AI Data & Analytics Engineer II — Samsara, Remote - Seattle
- Data Analyst II — OpenLoop Health, United States - Remote
- Lead Master Data Specialist — AST SpaceMobile, Midland, Texas, United States
- Data Analyst – Power BI — AST SpaceMobile, Midland, Texas, United States
- 2027 Summer Intern, PhD, Machine Learning - Simulation & Closed-Loop Training — Waymo, Mountain View, California, United States
- Analyst, Data Science - Burson — Burson, New York, New York, United States
| Workplace | Remote |
| Seniority | Not stated |
| Role | Data and machine learning |
| Countries | Argentina, Bolivia, Chile, Colombia, Dominican Republic, Ecuador, Egypt, Honduras, Mexico, Nicaragua, Panama, Peru, Paraguay, United States, Uruguay, South Africa |
| Languages | Python |
| Employment type | Contract |
| Contract | Contractor / B2B / freelance |
| Key facts | Stack: Python, LLM, CI/CD, Docker, Kubernetes, AWS, Terraform, PyTorch · Languages: English · Remote |
The full description is on the original posting. Labels are set automatically and can be wrong. About the data