PDS Health→
Machine Learning Engineer Intern
InternshipOn-site
Location
Irvine, CA
Salary
$36k–$52k/yr
Experience
Not specified
Posted
1 month ago
Skills
natural language processingmachine learningdeep learningpythonml frameworkslarge-scale datasetsstatistical analysiscommunication skillsteamworkindependent work
Job Description
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