Summer Internship - Machine Learning Engineer

🇺🇸 Austin, Texas
Posted 1 month ago
Expires May 29, 2026

About Us

We are establishing the first distributed Al infrastructure dedicated to personalized Al. The evolving needs of a data-driven society are demanding scalability and flexibility. We believe that the future of Al is distributed and enables real-time data processing at the edge, closer to where data is generated. We are building a future where a company's data and IP remains private and it's possible to bring large models directly to consumer hardware without removing information from the model.

About the Role

We are seeking a highly motivated and enthusiastic Machine Learning Engineer Intern to join our dynamic team for the summer. In this role, you will gain hands-on experience in developing and implementing machine learning models, data pipelines, and analytical solutions. Working alongside experienced professionals, you will have the opportunity to contribute to live projects and see the direct impact of your work.

Key Responsibilities

- Applied AI: Assist in designing, training, and evaluating machine learning models for real-world use cases.

- RAG Systems: Help build contextualized models and tools for efficient data ingestion and transformation.

- Research & Analysis: Perform exploratory data analysis and stay updated on the latest ML research, techniques, and tools.

- Collaborative Problem-Solving: Work closely with cross-functional teams (Data Scientists, Software Engineers, Product Managers) to define project requirements and deliver solutions.

- Documentation & Reporting: Prepare clear, concise technical documentation and report findings to relevant stakeholders.

- Quality Assurance: Contribute to code testing processes to ensure robust, high-quality deliverables.

Qualifications

- Currently enrolled in a Bachelor's, Master's, or PhD program in Computer Science, Engineering, Statistics, Mathematics, or a related field.

- Foundational knowledge of machine learning concepts, data structures, and algorithms.

- Proficiency in pro...

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