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Temporary Machine Learning Postdoc Jobs in Virginia

Smart Data

Data Scientist III

Chantilly, VA

$135K - $180K/yr

This role focuses on applying data science, machine learning, and data engineering techniques to ... temp-to-perm possible) - Schedule: Standard hours (40/week) - Work Location: On-site required ...

AKIVA AI, LLC

AI Research Scientist

Leesburg, VA · On-site

PhD in Computer Science, Machine Learning, Statistics, or related discipline (or equivalent ... Postdoctoral or industry research lab experience * Peer-reviewed publications, preprints, or ...

Williammary

Research Scientist

Gloucester Point, VA

$65K/yr

Experience integrating AI or machine learning approaches into environmental modeling * Experience ... Work closely with graduate students, postdoctoral associates, and visiting scientists * Participate ...

Socket.dev

CAD Designer

Richmond, VA · On-site

$26.75 - $36.75/hr

Rekor leverages computer vision, machine learning, and big data analytics to drive AI-enabled IoT ... Design temporary traffic control plans (TTCPs) for a variety of projects using CAD software ...

Kelly Services

Packaging Machine Operator

Williamsburg, VA · On-site

$18.50/hr

Packaging Machine Operator For those who want to keep growing, learning, and evolving. We at Kelly ... Temp to hire Why you should apply to be Packaging Machine Operator: * Competitive pay rate of $18 ...

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Temporary Machine Learning Postdoc information

What is a temporary machine learning postdoc?

A Temporary Machine Learning Postdoc is a fixed-term research position, typically held at a university or research institution, focused on advancing knowledge and techniques in machine learning. Postdoctoral researchers in this role work on specific projects, often collaborating with faculty, graduate students, or industry partners. The position is designed to provide advanced training and research experience after earning a PhD, usually lasting from several months to a couple of years. Temporary postdocs may contribute to publishing academic papers, developing algorithms, and mentoring students, while preparing for longer-term academic or industry careers.

What skills and qualifications are needed to thrive as a temporary machine learning postdoc?

To thrive as a Temporary Machine Learning Postdoc, you need a PhD in a relevant field, a solid grasp of machine learning theory, and strong programming skills (often in Python or R). Experience with tools such as TensorFlow, PyTorch, and high-performance computing environments, as well as a record of peer-reviewed research, is typically required. Strong analytical thinking, collaboration, and effective communication help you stand out in this research-intensive role. These skills are essential for advancing cutting-edge research, publishing impactful findings, and contributing to interdisciplinary projects.

What types of projects and collaborations can a temporary machine learning postdoc expect to engage in?

A Temporary Machine Learning Postdoc typically works on cutting-edge research projects, often contributing to ongoing studies or initiating novel investigations within the field. Collaboration is common, both within their immediate research group and with interdisciplinary teams, such as data scientists, domain experts, or industry partners. Postdocs may also mentor graduate students, present findings at conferences, and publish papers, gaining valuable experience that can lead to academic or industry roles. The environment is fast-paced and research-driven, offering opportunities for professional growth and expanding one's research portfolio.

What is the difference between Temporary Machine Learning Postdoc vs Data Scientist?

AspectTemporary Machine Learning PostdocData Scientist
CredentialsPhD in Computer Science, Data Science, or related fieldBachelor's or Master's in Data Science, Computer Science, or related field; often requires experience
Work EnvironmentAcademic or research institutions, labsCorporate, tech companies, startups
Employer & Industry UsageUniversities, research centersBusiness, technology, finance, healthcare
Search & Comparison IntentUnderstanding research-focused roles, academic opportunitiesIndustry roles, applied data analysis, business impact

The Temporary Machine Learning Postdoc is primarily research-oriented, often in academic or research settings, requiring a PhD. In contrast, a Data Scientist typically works in industry, applying data analysis and machine learning to solve business problems, often with a Bachelor's or Master's degree. Both roles involve machine learning skills but differ in environment, focus, and experience level.

What are the most commonly searched types of Machine Learning Postdoc jobs in Virginia?

The most popular types of Machine Learning Postdoc jobs in Virginia are:

What are popular job titles related to Temporary Machine Learning Postdoc jobs in Virginia?

For Temporary Machine Learning Postdoc jobs in Virginia, the most frequently searched job titles are:

What job categories do people searching Temporary Machine Learning Postdoc jobs in Virginia look for?

The top searched job categories for Temporary Machine Learning Postdoc jobs in Virginia are:

What cities in Virginia are hiring for Temporary Machine Learning Postdoc jobs?

Cities in Virginia with the most Temporary Machine Learning Postdoc job openings:

Temporary Machine Learning Postdoc jobs near you

Postdoctoral Research Associate, Machine Unlearning and Model Editing for AI Biosecurity

Charlottesville, VA ‱ On-site

University of Virginia
Colleges, Universities, and Professional Schools ‱ 10K+ employees
Learn more about University of Virginiaexternal

$60K - $75K/yr

Full-time

Medical, Dental, Vision, Life, PTO

Re-posted 26 days ago

Key responsibilities

  • Implement and compare machine unlearning and model editing methods, including gradient-based fine-tuning, representation-level edits, and inference-time steering

  • Design and run experiments to measure how interventions affect benchmark scores and real-world task performance, producing safety-utility curves

  • Lead engineering of the open-source UBS-Bio evaluation suite, including baselines, metrics, and documentation

University Of Virginia rating

7.9

Company rating: 7.9 out of 10

Based on 35 frontline employees who took The Breakroom Quiz

Job description

About the School
The University of Virginia School of Data Science, the first of its kind in the nation, advances discovery, innovation, and societal impact through collaborative, open, and responsible data science research and education. Founded in 2019, the School brings together expertise across business, computation, engineering, humanities, law, mathematics, social sciences, and statistics to address complex, real-world challenges. Its academic offerings include a B.S. in Data Science, an undergraduate minor, residential and online M.S. in Data Science programs, and a Ph.D. in Data Science, all designed to prepare students for a rapidly evolving data-driven world.
About the Position
This position develops and evaluates machine unlearning and model editing methods that selectively reduce hazardous biological capabilities in AI systems while preserving beneficial scientific functions . The researcher reports to Assistant Professor Tom Hartvigsen and will work closely with other SDS faculty members including Chirag Agarwal , and Stephen Turner, and works with faculty in interpretability and with a laboratory partner that leads adversarial red teaming. The role centers on implementing , innovating, and comparing model editing and unlearning methods , measuring safety - -utility tradeoffs against both benchmarks and realistic task batteries, and leading technical development of an open evaluation suite for AI biosecurity. Strong f amiliarity with biology and biosecurity is important , as the work targets biological capabilities and connects to a human-subjects evaluation running in parallel.
Key Responsibilities
  • Implement and compare machine unlearning and model editing methods, including gradient-based fine-tuning, representation-level edits, and inference-time steering

  • Design and run experiments that measure how interventions affect benchmark scores and real-world task performance, producing safety-utility curves

  • Develop adversarial testing protocols with the laboratory partner, including prompt-based jailbreaks, fine-tuning recovery, and ensemble attacks

  • Lead engineering of the open-source UBS-Bio evaluation suite, including baselines, metrics, and documentation

  • Support interpretability analyses that identify which model representations encode hazardous versus beneficial capabilities

  • Prepare and present manuscripts and publish and maintain reproducible code releases

Minimum Qualifications
  • Doctoral degree (PhD or equivalent) in data science, computer science, machine learning, or a related field, completed at the time of hire

  • Strong programming in Python and hands-on experience with modern ML frameworks such as PyTorch and Hugging Face Transformers

  • Track record of publications in machine learning, natural language processing, and/or biosecurity

  • Demonstrated experience training, finetuning, or post-training for large language models

  • Software engineering practices that support reproducible and reusable research tools

Preferred Qualifications
  • Understanding of biology, biosecurity, or dual-use research considerations

  • Experience with machine unlearning, model editing, or related capability-mitigation methods

  • Experience with mechanistic interpretability or representation analysis

  • Familiarity with adversarial robustness, red-teaming, or jailbreak evaluation

  • Experience releasing and maintaining open-source ML evaluation tooling

  • Familiarity with secure computing environments and controlled-access model arrangements

Anticipated Salary: $60,000 - $75,000 per year
Anticipated Start Date: September 1, 2026
Health and Other Benefits
(visit Health and Other Benefits for additional information)
  • UVA Health Plan: the choice between 3 different health plans

  • Vision Coverage

  • Dental Plan

  • Benefit Savings Plans

  • Life Insurance

  • Disability Benefits

  • Paid Time Off: starting with 22 days of time off per year, 12 or more holidays, 8 weeks parental leave

Education Benefits (visit Education Benefits for additional information)
After six months of employment, full-time and part-time (20+ hours) employees in a benefits-eligible position are offered options of:
  • Use of up to $5250 per calendar year towards a for-credit degree program or for-credit certificate program

  • Use of up to $2000 of the total $5250 noted above per calendar year for professional development including job-related training, conferences, and initial certificate exams.

Position Details
This position will remain open until it is filled. This is a full-time in-person position at the School of Data Science at the University of Virginia in Charlottesville, VA. The initial appointment is for one year; however, the appointment may be renewed for an additional year contingent upon funding and satisfactory performance. This is an exempt level, term-limited (restricted), benefited position.
Application Process
Please apply online , and search for R0084978.
Complete an application online and attach:
Cover letter detailing your interest and relevant experience to this position Resume or CV Two letters of recommendation with contact information
Applications that do not contain all required documents will not receive full consideration.
Internal applicants: Search and apply for jobs on the UVA Internal Careers website .
References will be completed via direct reach. Please plan to provide at least three references when applying.
A background check is required and will be conducted per university policy prior to the first day of employment.
For questions about the position , contact Associate Professor Stephen D. Turner at sdt5z@virginia.edu .
For questions about the application process, please contact Daniel Strong, Senior Human Resources Recruiter, at das6zb@virginia.edu .
For more information about UVA and the Charlottesville community, please see www.virginia.edu/life/charlottesville and https://embarkcva.com/ .
The University of Virginia is an equal opportunity employer. All interested persons are encouraged to apply, including veterans and individuals with disabilities.
MINIMUM REQUIREMENTS
Education: Doctoral degree
Experience: None
Licensure: None
PHYSICAL DEMANDS
This is primarily a sedentary job involving extensive use of desktop computers. The job does occasionally require traveling some distance to attend meetings, and programs.
The University of Virginia is an equal opportunity employer. All interested persons are encouraged to apply, including veterans and individuals with disabilities. Learn more about UVA's commitment to non-discrimination and equal opportunity employment .

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About University of Virginia

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The University of Virginia is distinctive among institutions of higher education. Founded by Thomas Jefferson in 1819, the University sustains the ideal of developing, through education, leaders who are well-prepared to shape the future of the nation.

Industry

Colleges, universities, and professional schools

Company size

10,000+ Employees

Headquarters location

Charlottesville, VA, US

Year founded

1819

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