AI/ML Engineering Intern

AI/ML Engineering Intern About Globali.ai Globali.ai is building immigration infrastructure for global hiring. The platform helps employers evaluate visa feasibility before interviews, automate immigration case preparation, monitor compliance risks, and collaborate with immigration counsel. About the Internship Globali.ai is seeking an AI/ML Engineering Intern to support the development and evaluation of its immigration intelligence platform. You will work with engineers and immigration-domain experts on practical AI problems involving eligibility analysis, document understanding, retrieval, structured reasoning, and explainability. Location Location: San Francisco, CA, US FULL_TIME Responsibilities Assist with AI workflows that evaluate immigration and visa scenarios. Build and test retrieval pipelines grounded in immigration policies and internal knowledge sources. Help create structured prompts, tool-calling workflows, and machine-readable outputs. Develop test datasets for eligibility assessments, document review, and policy interpretation. Evaluate model responses for accuracy, consistency, completeness, and unsupported conclusions. Support experiments in document extraction, classification, summarization, and evidence matching. Analyze model failures and improve prompts, retrieval quality, validation rules, and safeguards. Build scripts or dashboards for tracking evaluation results and regressions. Document experiments, findings, limitations, and recommendations. Required Qualifications Pursuing or recently completed a degree in computer science, data science, machine learning, AI, or a related field. Working knowledge of Python. Familiarity with machine learning, NLP, or large language models. Understanding of APIs, JSON, data processing, and software-development fundamentals. Strong analytical and communication skills. Interest in responsible AI, explainability, and human-in-the-loop systems. Preferred Qualifications Experience with LLM APIs, embeddings, vector databases, or retrieval-augmented generation. Familiarity with pandas, scikit-learn, PyTorch, or similar tools. Experience creating evaluation datasets or automated test suites. Exposure to document intelligence, knowledge graphs, or rule engines. Interest in legal technology, compliance, HR technology, or global mobility. Building AI systems for regulated enterprise workflows. Designing evaluations for factual accuracy and reliability. Translating complex domain rules into technical systems. Understanding how AI supports expert legal review. Contributing to production-oriented product and engineering decisions. What Success Looks Like Model weaknesses are identified and documented clearly. AI outputs become more consistent, evidence-based, and explainable. Experiments lead to practical product improvements. Work is organized, reproducible, and useful to the broader team. Globali.ai is an equal opportunity employer. #J-18808-Ljbffr Globali