Machine Learning Engineer Intern

Summary: PDS Health is seeking a Machine Learning Engineer Intern to join their Summer Intern Program, which offers undergraduate students valuable experience in a large multi-state employer's operations. The intern will assist in designing evaluation frameworks for language models and collaborate with engineers to improve model performance. Responsibilities: - Assist with the design and implementation of evaluation frameworks for large language models (LLMs) and persona-based NLP systems - Develop quantitative and qualitative metrics to assess full duplex model behavior across diverse personas, tasks, and conversational contexts - Conduct benchmarking studies comparing baseline and experimental models, including behavior associated with speech, such as when to pause, interrupt or backchannel - Perform error analysis to identify failure modes such as persona drift, bias, confabulations, and robustness issues - Collaborate with AI/ML engineers to translate evaluation findings into model improvements - Author technical reports, research papers, and internal documentation summarizing experimental results and insights - Contribute to dataset curation and synthetic data generation for persona-driven conversational NLP tasks - Ensure evaluation methodologies follow best practices in reproducibility, fairness, and ethical AI guidelines - Other duties as assigned by Management Required Qualifications: - Current or recent enrollment in an accredited postgraduate degree program in Computer Science, Machine Learning, NLP, or a closely related field - Strong foundation in natural language processing, machine learning, and deep learning (e.g. large language models, transformers, self-guided learning) - Proficient in Python and ML frameworks such as PyTorch, TensorFlow, JAX, or similar - Familiarity with LLM tooling and ecosystems (e.g. Hugging Face, OpenAI APIs, LangChain, Dify) - Experience working with large-scale datasets and distributed or GPU-based computing environments - Knowledge of research methods, including statistical analysis and experimental design - Strong written and verbal communication skills, with the ability to present technical findings to both research and engineering audiences - Ability to work independently and as part of a team Preferred Qualifications: - Publication record or experience contributing to academic or industry research projects - Interest in model alignment, personalization, fairness, and responsible AI practices Required Skills: Natural Language Processing, Machine Learning, Deep Learning, Python Important Skills: ML Frameworks, Large-scale Datasets, Statistical Analysis Nice-to-Have Skills: Communication Skills, Teamwork, Independent Work