Machine Learning Engineer Intern

PDS Health • Irvine, CA

6h • $17 - $25 • Onsite

About The Position

Now is the time to join PDS Health. You will have opportunities to learn new skills from our team of experienced professionals. If you're ready to take your career to the next level and gain valuable experience, apply today!

The PDS Health Summer Intern Program is a 10-week, on-site, full-time, paid internship that provides undergraduate students with invaluable insight and experience into the operation of a large multi-state employer.

Requirements

• 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

Nice To Haves

• Publication record or experience contributing to academic or industry research projects
• Interest in model alignment, personalization, fairness, and responsible AI practices

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

What This Job Offers

• Job Type: Full-time
• Career Level: Intern