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# AI, Data and Platform Engineering

- **Company:** Relativity Space, Inc.
- **Location:** United States
- **Salary:** $115,000.0 - $173,000.0
- **Contract:** Internship / Graduate position
- **Skills:** Amazon Web Services, Software Applications, Data Structures, Python (Programming Language), PostgreSQL, MongoDB, Software Tools, Search Technologies, Software Engineering, TypeScript, ReactJS, Retrieval-Augmented Generation, Large Language Models, Apache Spark, Kubernetes, Information Technology, Terraform, Golang
- **Published:** August 23, 2026
- **Apply:** https://www.dice.com/job-detail/4fc2aa37-0552-48c3-a297-500c7b475189

## About the Role

* Bachelor's degree or higher in Computer Science or a related engineering field (Computer, Software, Electrical, Aerospace).
 * Strong computer science foundations: data structures, algorithms, systems, and clean, testable code
 * Hands-on experience building with large language models, whether through coursework, projects, or self-directed work
 * Proficient in at least one language you love, and eager to learn new ones
 * Curious, fast-learning, and motivated to work directly with engineers and operators on the factory floor

Nice to haves but not required:

 * 1+ years of professional experience, including internships, research, or substantial personal and academic projects you have shipped
 * Experience building agents, retrieval-augmented generation, or LLM evaluation pipelines
 * Familiarity with data engineering tools and modern data stacks
 * Exposure to manufacturing, hardware, robotics, or other physical-world domains
 * Contributions to open-source projects or published research

## Description

You will help build AI systems used by engineers and operators across the company, working across the full software development life cycle: concept, design, implementation, and ongoing iteration. Build AI-powered applications and agents on top of foundation models, and make them reliable in production. Follow agile development practices and ship quality software that is continuously integrated and deployed. Solve complex problems with simple solutions. Work directly with users and stakeholder teams to define requirements, implement solutions, and iterate. Technologies we use: Python, React, TypeScript, Go. Foundation models (Claude and others), agent and orchestration frameworks, retrieval and vector search, LLM evaluation tooling. Spark, Iceberg, DuckDB, Redshift, DBT, Postgres, Mongo. AWS, Kubernetes (cloud and on-prem), Terraform, Helm.


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