AIMachine Learning Software Engineering Intern

Support the design development and deployment of agentic AI systems operating in secure air-gapped and edge environments. Work alongside senior engineers to build and test LLM-based pipelines contribute to agentic workflow development and assist with model optimization for constrained and offline deployment targets. Gain hands-on experience with real production-oriented AI systems at the intersection of machine learning systems engineering and infrastructure-aware deployment.

Responsibilities

• Contribute to the design and implementation of agentic AI workflows including multi-agent orchestration tool use and reasoning loops
• Assist with the deployment of LLM-based systems in air-gapped on-premises and edge environments under the guidance of senior engineers
• Support the build-out of secure inference pipelines designed to operate without external network access
• Write clean modular code that integrates ML components into broader software systems and pipelines
• Run and test models on edge hardware platforms and constrained compute targets; assist with performance and memory optimization
• Support model fine-tuning and distillation experiments including data preparation training runs and evaluation
• Contribute to reproducible engineering workflows including version control containerization and structured testing
• Author and maintain documentation pertaining to deployment processes system configurations and experiment results
• Troubleshoot issues across the stack from model behavior through API layer through infrastructure and report findings clearly
• Assist with hardware configuration tasks for GPU workstations and servers as needed with guidance provided
• Engage with senior engineers to understand system changes contribute to evaluations and provide feedback for continuous improvement

• Must currently be pursuing a Bachelors degree in Computer Science Computer Engineering Software Engineering or a related technical discipline
• Strong Python programming skills
• Understanding of basic software engineering principles code modularity debugging and testing
• Understanding of machine learning fundamentals and neural network basics
• Familiarity with Git and modern software development workflows
• Familiarity with REST APIs and basic software integration concepts
• Ability to work independently prioritize tasks and document work clearly
• Effective written and verbal communication skills

Preferred Qualifications

• Experience with LLM inference or serving frameworks such as vLLM Ollama or Hugging Face Transformers
• Any hands-on experience with model fine-tuning or distillation including course projects or personal experiments
• Familiarity with agentic frameworks such as LangChain LangGraph AutoGen or similar
• Experience deploying or running software in constrained offline or non-cloud environments
• Exposure to containerization tools such as Docker
• Any familiarity with GPU setup or configuration for ML workloads; curiosity about hardware is welcome deep expertise is not expected
• Interest in or exposure to edge hardware platforms such as NVIDIA Jetson Raspberry Pi or similar devices