The Applied Research Laboratory for Intelligence & Security (ARLIS) at the University of Maryland is a University-Affiliated Research Center (UARC) dedicated to advancing research, innovation, and technology transition to improve decision making for U.S. national security. ARLIS combines deep scientific expertise with operational insight to address challenges in intelligence analysis, cybersecurity, artificial intelligence / machine learning, quantum science, and human-machine teaming. Researchers, scientists, engineers, and analysts at ARLIS collaborate with government agencies, industry partners, and academic institutions to deliver actionable insights and transformative solutions through research and development. Employees at ARLIS work on projects of critical importance, contribute directly to the nation’s security, and are supported by a culture that values integrity, collaboration, and professional growth.
The AI Research Assistant will assist the AI/Machine Learning lead for DE Bioeffects project in their efforts to develop and refine the AI/ML backed sensemaking technology for the repository. They will attend project meetings at the request of the PI, co-PIs, and AI/ML lead, and may be asked to take technical notes during meetings. They will maintain a collaborative work style and help the AI/ML lead solve problems with the large interdisciplinary research team.
Physical Demands:
Sedentary work performed in a normal office environment; exerts up to 10 pounds of force occasionally and/or negligible amount of force frequently or constantly to lift, carry, push, pull or otherwise move objects, including the human body. Ability to attend meetings both on and off campus. Spending long hours in front of a computer screen.
Licenses/ Certifications: N/AMinimum Qualifications
Education:
- Currently enrolled in a Bachelor’s, Master’s, or Doctoral degree program at an accredited college or university in Computer Science, Data Science, Computational Linguistics/Natural Language Processing, Information Science, Electrical and Computer Engineering, or a closely related field.
Experience:
- Demonstrated hands-on experience — through coursework, research, internship, or a personal project — building and evaluating retrieval and language-model systems, including at least one retrieval system built end to end and at least one model the candidate trained or fine-tuned themselves.
Must be able to obtain a US security clearance. If selected, must meet the requirements for access to classified information and will be subject to a government security clearance investigation that includes criminal and credit history checks, as well as verification of U.S. citizenship, birth, education, employment, and military history. Final offer is contingent upon the candidate’s ability to successfully obtain the necessary interim Secret security clearance, as determined by ARLIS, prior to commencing employment.
Knowledge, Skills, and Abilities:
- Proficiency in Python, including the ability to write modular, re-runnable, and documented code.
- Working familiarity with the Linux command line and with version control using Git.
- Familiarity with at least one modern machine-learning or natural-language-processing toolkit — for example, PyTorch, Hugging Face Transformers, or sentence-transformers.
- Ability to learn unfamiliar tools independently from documentation and example code, and to raise blockers promptly rather than working around them silently.
- Ability to communicate clearly in writing, to work collaboratively as part of an interdisciplinary research team, and to use standard office productivity software.
Preferences:
Education:
- Graduate-level study in Computer Science, Natural Language Processing, Machine Learning, Information Science, or a related field.
Experience:
- Domain adaptation of retrieval models — fine-tuning an embedder or reranker on in-domain data; continued pretraining on a domain corpus.
- Information extraction: NER, entity linking, relation extraction — including fine-tuning extraction models on a labeled gold set.
- Knowledge graphs: building a citation/affiliation/funding graph and querying it; traversal, community detection; Neo4j or NetworkX.
- GraphRAG, or a considered view on RAG vs. GraphRAG.
- NLI / entailment or groundedness scoring.
- Constrained or schema-guided decoding.
- Multi-GPU or distributed training; experiment tracking.
- Layout-aware PDF parsing and OCR.
- REST API development (FastAPI / Flask); DevOps, CI/CD.
- Comfort working independently and collaboratively in a fast-paced, evolving environment.
- Strong organizational skills and attention to detail.
- Active or eligible for a security clearance.
Required Application Materials: Cover Letter, Resume, List of References
Best Consideration Date: N/A
Posting Close Date: N/A
Open Until Filled: Yes
Offers of employment are contingent on completion of a background check. Information reported by the background check will not automatically disqualify anyone from employment. Before any adverse decision, the finalist will have an opportunity to provide information to the University regarding disclosable background check information. The University reserves the right to rescind the offer of employment or otherwise decline or terminate employment if the information reported by the background check is deemed incompatible with the position, regardless of when the background check is completed.
Employment EligibilityThe successful candidate must complete employment eligibility verification (on Form I-9) by presenting documents that establish identity and work authorization within the timeframe required by federal immigration law, and where applicable, to demonstrate renewed employment authorization. Failure to complete employment eligibility verification or reverification within the timeframe set forth by law may result in suspension or termination of employment.
EEO StatementThe University of Maryland, College Park is an Equal Opportunity Employer. All qualified applicants will receive equal consideration for employment. Please read the University’s Equal Employment Opportunity Statement of Policy.
Title IX Non-Discrimination NoticeResourcesLearn how military skills translate to civilian opportunities with O*Net Online
There are some positions that are not advertised on this career site as the search is being managed by a Search Firm.
Please visit the link below to see these available opportunities:
Search Firm Managed Vacancies
Skills Required
- Currently enrolled in a Bachelor's, Master's, or Doctoral degree program at an accredited college or university in Computer Science, Data Science, Computational Linguistics/Natural Language Processing, Information Science, Electrical and Computer Engineering, or a closely related field.
- Hands-on experience building and evaluating retrieval and language-model systems through coursework, research, internship, or a personal project.
- Built at least one retrieval system end to end.
- Trained or fine-tuned at least one machine-learning or language model independently.
- Proficiency in Python, including writing modular, re-runnable, and documented code.
- Working familiarity with the Linux command line.
- Working familiarity with Git version control.
- Familiarity with at least one modern machine-learning or natural-language-processing toolkit, such as PyTorch, Hugging Face Transformers, or sentence-transformers.
- Ability to learn unfamiliar tools independently and raise blockers promptly.
- Clear written communication and ability to collaborate on an interdisciplinary research team.
- Ability to use standard office productivity software.
- Graduate-level study in Computer Science, Natural Language Processing, Machine Learning, Information Science, or a related field.
- Experience with domain adaptation of retrieval models, including fine-tuning embedders or rerankers and continued pretraining.
- Experience with information extraction, including named entity recognition, entity linking, and relation extraction.
- Experience building and querying knowledge graphs using Neo4j or NetworkX.
- Knowledge of GraphRAG and retrieval-augmented generation.
- Experience with natural language inference, entailment, or groundedness scoring.
- Experience with constrained or schema-guided decoding.
- Experience with multi-GPU or distributed training and experiment tracking.
- Experience with layout-aware PDF parsing and OCR.
- Experience developing REST APIs with FastAPI or Flask.
- Experience with DevOps and CI/CD.
- Active security clearance or eligibility to obtain one.
- Ability to obtain an interim Secret security clearance before commencing employment.
What We Do
The University of Maryland, College Park offers federal student loans and covers tuition and fees for eligible students.
