Part-Time ProgrammerThe Department of Computer Science and Engineering within the College of Engineering is seeking applicants for a part-time programmer.The role: Help us build a focused, sharp system that turns peer-reviewed nutrition literature into transparent, evidence-based recommendations. You'll implement the Extract, Transform Load (ETL) pipeline from OpenAlex, fine-tune and wire up transformer models for relation extraction, and ship a production-grade recommendation/generative layer backed by a provenance-rich knowledge graph.What you'll do:Stand up and own a PubMed or OpenAlex ETL that ingests open-access articles, normalizes metadata, and keeps our corpus fresh.Use and/or fine tune transformer models (e.g., BERT variants) to extract semantic triples (like: (ingredient)–(biolink:ameliorates_condition)–>(health condition)); build evaluation and error-analysis loops.Implement a ranking layer that blends evidence strength (study design, sample size, effect size) with model confidence.Build the recommendation/generative service that balances constraints (evidence score, compatibility, regulatory limits) and exposes a clean API.Construct/maintain a knowledge graph that links every recommendation back to source papers (full provenance) and supports plain-language evidence summaries.Collaborate tightly with PI and domain scientists; deliver milestones on a fast, 12-month pilot timeline.Core stack we use (and you're comfortable with):Python 3.x; modern NLP/ML (PyTorch or TensorFlow, Hugging Face, scikit-learn); data/ETL tooling (pandas, spaCy, Pydantic, Airflow/Prefect).APIs/services: RESTful design, auth, pagination, retries, structured logging, unit/integration tests, CI.Storage/search: Postgres + vector/embedding store; graph DB experience welcome.DevOps basics: containers, reproducible envs, simple local deploys, secrets management.Nice to have:Deep NLP experience (relation extraction, weak supervision, prompt/adapter tuning).Semantic KGs (RDF/OWL, Neo4j/graph tooling), ontology work, and/or the Biolink Model.Experience with biomedical text corpora and literature mining.You've shipped scrappy, reliable research-to-prod systems before.What you bring:3+ years professional Python and ML/NLP engineering, or equivalent portfolio.Strong engineering hygiene (tests, docs, code review) and product sense.Clear, direct communication in a remote team.Bonus: prior work at the intersection of ML + biosciences/clinical data.Logistics & pay:Fully remote (U.S.); office space available at Penn State for hybrid/in-person if preferred.Part-time at $57/hour, 20 hours/week, 50 weeks. Continuation beyond 50 weeks depends on renewal/next-round funding.Please submit a brief cover letter and resume/CV.For more information on restrictions for part-time remote employment locations: Notice to Out of State Applicants