Data & Hardware Operations Intern

About the role

The AI Engines team is responsible for product-oriented research, data collection, and ML model development for Wi-Fi-based motion sensing. This is a high-ownership role with deliberate breadth. You will be the person who keeps collection running and the hardware healthy, freeing our engineers and researchers to focus on models and product.

Responsibilities

• Configure, provision, and maintain device deployments across our data collection fleet.
  • This includes connecting devices to routers and onboarding them in their respective apps.
  • Manage and troubleshoot collection sets; diagnose and resolve issues quickly, including general IT tasks such as logging into router back-ends, IP configuration, and basic network troubleshooting.
  • Run platform performance comparisons and device compatibility testing across our hardware portfolio.
• Develop, update, and maintain standard operating procedures (SOPs) for device onboarding and deployment so setup is repeatable and consistent across platforms.
• Build and host data collection events; coordinate with external data collection partners and field testers to execute against collection plans.
• Maintain device and tester inventory so collection coverage aligns with ML model development priorities and product improvement ideas.
• Keep the team's automated data pipeline running, and perform data quality checks and session-level curation on incoming CSI to meet quality and scope needs.
• Write and run test plans for collection and validation.
• Dogfood our models daily by running live deployments in-office, surfacing real-world sensing issues back to the team.
• Contribute to embedded integration (C/C++) and ML platform / MLOps tasks as your skills develop.
• Participate in agile workflows: Sprint planning, code reviews, and stand-ups. Present technical findings to the team.

Requirements

• Able to be on-site in the Rockville, MD area; this role manages physical hardware and cannot be fully remote.
• Currently pursuing or recently completed a Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, Computer Science, Information Technology, or a closely related discipline. Candidates must have completed at least three years of undergraduate study by the start of employment.
• Comfortable with networking fundamentals (e.g. routers, IP configuration, device back-end access, and basic troubleshooting).
• Hands-on experience with at least one programming language (MATLAB, C/C++, or Python).
• Detail-oriented, self-directed learner who thrives in collaborative teams and can diagnose issues and make effective decisions in ambiguous, evolving technical situations.

Preferred Qualifications

• Embedded / systems programming: C/C++ experience on microcontrollers, SoCs, or resource-constrained platforms (ARM Cortex, RTOS, bare-metal).
• Supports the embedded/QA growth track.
• MATLAB: Coursework or project experience, for our data processing scripts.
• Signal processing: Coursework or projects in DSP, wireless communications, or related areas (FFT, filtering).
• Machine learning: Familiarity with ML frameworks (PyTorch, ONNX, TensorFlow Lite) or data-quality practices for AI/ML.
• Data collection & tooling: Structured data collection and logging practices; familiarity with Airtable or similar.
• AWS & agile tooling: Exposure to AWS (S3, etc.) and Atlassian tools (Jira, Confluence) in a team-based environment.