Job Title: ML/AI Engineering Intern (OpenTeams Product Team)

Two stage hiring process:

1. Application Deadline: April 9th, 2026 by midnight
2. GW OSPO will choose 3-5 applicants to forward to OpenTeams for final interviews.

Internship Dates: May 18th - August 15th, 2026
Location: Remote. Must be US-based. Must be authorized to work in the U.S.
Commitment: 40 hrs p/week
Pay Rate: $18 p/hour


ABOUT THE ROLE
OpenTeams Product Team incubates and supports client-facing and internal products.

WHAT YOU'LL DO
1. Build AI applications that drive real business outcomes.

• Contribute to the design and development of GenAI applications (e.g., copilots, workflow automation, decision support) using modern LLM stacks.
• Support the implementation of agentic workflows where they add clear value (e.g., tool use, multi-step execution, human-in-the-loop controls), with attention to reliability, safety, and clear failure modes.
• Assist in building robust agent capabilities including context engineering, memory/state management (short-term and long-term), orchestration, routing, and tool integration patterns.

2. Build and apply data science and machine learning capabilities

• Contribute to ML solutions end-to-end: data preparation, feature engineering, model selection, training, validation/testing, and performance analysis.
• Apply appropriate ML methods for the problem, spanning classical ML and deep learning (including sequence, text, and image models when relevant).
• Develop working knowledge of modern deep learning concepts, including transformer fundamentals and LLM pre-training vs post-training concepts (e.g., instruction tuning, preference optimization).

3. Engineer for real delivery: POC → MVP → production

• Write clean, testable, maintainable code and ship AI services through the full SDLC: build → test → deploy → monitor → iterate.
• Support implementation of MLOps and GenAIOps practices: CI/CD, reproducibility, environment parity, model/prompt/agent versioning, and operational readiness.
• Contribute to evaluation and observability for GenAI and agentic systems: tracing and instrumentation, regression test suites, automated scoring where appropriate, and iteration loops for prompt/policy optimization.
• Gain exposure to secure enterprise deployment practices, including access controls, auditability, data handling for sensitive/PII data, and responsible AI guardrails.
• Contribute to reusable components and accelerators (templates, evaluation harnesses, connectors, orchestration patterns) that scale across client contexts.

WHAT WE'RE LOOKING FOR

• Solid understanding of software engineering foundations (principles, design patterns, and best practices). Experience in Python is essential.
• Experience in one of the following areas: Machine Learning, MLOps, Data Engineering, Generative AI, or Agentic AI.
• Proven ability to analyze complex technical problems, propose solutions, and drive them to successful implementation.
• Exceptional verbal and written communication skills, with the ability to articulate complex technical concepts clearly to diverse audiences.
• Ability to work effectively with cross-functional teams.
• Bonus points: Active participation and contributions to open source (e.g., contributing to open source projects, presenting at conferences, organizing meetups, etc.).