About The Role

Job Description Summary

Organization's Summary Statement

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 Data Engineering Research Assistant [TW2.1]works directly with project teams to build and run Python-based data pipelines, prepare, load, and validate data in databases, and help implement search and retrieval components under the guidance of senior technical staff.

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/A

Minimum Qualifications

Education

Bachelor’s degree in Computer Science, Data Science, Information Systems, Engineering, Mathematics, or a related field from an accredited college or university.

Experience

Professional or substantial project-based experience programming in Python.
Experience designing and implementing data pipelines or ETL/ELT jobs that read from one or more sources, transform data, and load into a database.
Hands-on experience with at least one database (document or relational), including schema design, writing queries, and validating loaded data.
Experience using Linux command-line tools and working in a Git-based workflow (branches and pull requests).
Experience writing and executing tests in Python (e.g., using Pytest).
Experience using Docker or similar containerization tools to run or troubleshoot applications.

Knowledge, Skills, and Abilities

Ability to quickly internalize and work within modular codebases and design re-runnable, configurable jobs.
Conceptual understanding of embeddings and vector similarity search, or prior experience with information retrieval / NLP projects.
Familiarity with tools and technologies such as MongoDB, PostgreSQL, JSON Schema, Qdrant, pgvector, FAISS, or sentence-transformers (experience with some subset is acceptable).
Ability to build or confidently learn to build REST APIs with FastAPI or Flask, including basic authentication.
Strong analytical and problem-solving skills, including the ability to profile datasets, identify anomalies, and communicate implications clearly.
Strong written communication skills, including concise technical documentation and status reporting.
Demonstrated discipline and care when working with sensitive or controlled data; familiarity with data classification, provenance, and access-control concepts is a plus.
Ability to work both independently and collaboratively in a multidisciplinary research environment.
Skill in the use of Microsoft Office products.
Skill in troubleshooting system errors.
Ability to multi-task and prioritize assignments.
Ability to analyze situations and determine the best recourse for response.

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.

Additional Job Details

Preferences

Experience

Relevant technical certifications (e.g., cloud, database, or DevOps) are welcome but not required.
Experience contributing to a retrieval-augmented generation, search system, or similar information-retrieval project (academic, internship, or research).
Experience with Pytest or similar tools for testing Python code.
Experience using Docker or similar tools to run or troubleshoot applications.
Exposure to DevOps or CI/CD concepts (e.g., automated testing, basic deployment workflows).
Exposure to data classification, provenance, or access-control concepts in a research or operational context.
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

Department
VPR-Applied Research Lab for Intelligence & Security

Worker Sub-Type

Staff Contractual (C1) (Fixed Term)

Salary Range

$23-$50

Background Checks

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 Eligibility

The 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 Statement

The 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.