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About This Role
Affiliated Office Address
Baltimore, MD, United States
Requisition ID
121988
Date Created
July 31, 2026
Job Family
Administrative Services
Job Subfamily
General Admin Suppt
Job Function
Clerical/Administrative Support
Exempt Status
Exempt
Shift Type
Full Time
Schedule
M\-F, 37\.5 hrs wkly
Worksite
02\-MD:Mount Washington Campus
Work Modality
Hybrid: On\-site 60\-89% of hours worked (Ex: 3\-4 out of 5 days/week)
The Johns Hopkins Data Science and AI Institute (DSAI) seeks an *Administrative Specialist* to provide high\-level administrative, operational, and program support for a growing interdisciplinary institute advancing data science and artificial intelligence across Johns Hopkins. This position will support DSAI's program management team of four Program Managers and will help coordinate the administrative infrastructure behind institute programs, funded initiatives, events, meetings, communications, and cross\-university collaborations. The Administrative Specialist will work closely with institute leadership, faculty, staff, students, trainees, internal Johns Hopkins partners, and external collaborators to ensure timely, accurate, and professional execution of program and office operations.
The Administrative Specialist provides varied administrative support ranging from standard to complex for an individual, group, and/or unit requiring high level expertise and independent decision making. Works on administrative assignments that require research, initiative, independent discretion, and specialized knowledge and abilities. Leads or assists with ad\-hoc or recurring projects. Responsibilities require significant collaboration and coordination with others within and outside of the unit and extensive knowledge of the organization.
Specific Duties \& Responsibilities
- Independently manage complex calendars and meeting schedules based on an understanding of shifting priorities.
- Provide preparation for meetings, presentations, and discussions by gathering critical details to facilitate timely responses and task management.
- Support staff management and team meetings, and provide follow\-up on action items.
- Anticipate departmental needs by prioritizing incoming work to ensure timely and effective resolution and following up with deadlines, drafts, reminders.
- Lead or significantly contribute to recurring or ad\-hoc projects, including providing support or guidance to other staff.
- Assist with planning and conduct of events as needed.
- Perform general office management necessary for efficient operations. e.g. assisting with space issues, room reservation requests, technology needs, etc.
- Ensure timely processing and submission of travel reimbursements, online payments, purchase orders, and non\-employee expense reimbursements.
- Locate and compile information to format and produce reports, graphs, tables, records, and other sources of information.
- Responsible for answering questions, providing guidance, and disseminating information.
- Interpret and communicate operating policies.
- Proactively identify and assist with the resolution of administrative problems.
- Maintain high\-level knowledge of the informal and formal department goals, standards, policies, and procedures including familiarity with other departments in the school/division.
- Other duties as assigned.
*In addition to the duties described above*
- Provide administrative and program coordination support to four DSAI Program Managers responsible for signature programs, funded initiatives, workshops, committee and advisory board activities, and other institute priorities; assist with scheduling, agendas, materials, notes, action\-item tracking, and follow\-up.
- Coordinate logistics for DSAI programs and events, including room reservations, hybrid meeting support, travel arrangements, catering, procurement, vendor coordination, attendee communications, registration support, and expenditure tracking.
- Support administrative and financial tracking processes for DSAI\-funded programs and initiatives, including proposal intake, award coordination, collaborator meetings, compliance documentation, expenditure tracking, budget\-to\-actual monitoring, burn\-rate reporting, deliverable tracking, and maintenance of accurate program records.
- Prepare, organize, and maintain program materials, reports, presentations, web or communications content, spreadsheets, and shared project documentation used by Program Managers, institute leadership, faculty, and internal and external partners.
- Help strengthen standard operating procedures, shared calendars, tracking tools, and administrative workflows that support consistent service, timely communication, and effective coordination across DSAI programs.
Minimum Qualifications
- Bachelor’s Degree.
- Four years of progressively responsible administrative experience, with experience working on special projects and assignments.
- Additional education may substitute for required experience and additional related experience may substitute for required education beyond HS diploma/graduation equivalent, to the extent permitted by the JHU equivalency formula.
Preferred Qualifications
- Strong organizational, written communication, calendar management, meeting coordination, data tracking, and customer\-service skills, with the ability to manage multiple priorities and deadlines across several programs and stakeholders.
- Experience providing administrative or program support in higher education, academic research, nonprofit, or complex matrixed environments.
- Experience supporting program managers, faculty, committees, advisory boards, sponsored or internally funded projects, large meetings, workshops, or events.
- Familiarity with Johns Hopkins systems and processes, including SAP, Concur, procurement, P\-Card, travel, room scheduling, and web or event communication tools.
- Comfort using AI\-enabled productivity tools such as ChatGPT, Claude, Gemini, or similar tools to support drafting, organization, summarization, or workflow efficiency, consistent with university policy.
Technical Qualifications \& Specialized Certifications
- Highly proficient with Microsoft Office programs including Outlook, Word, Excel and PowerPoint, Teams, Adobe Acrobat, and collaboration or project\-tracking platforms such as Asana, SharePoint, or similar tools.
- .No specialized certification is required. Training or coursework in project coordination, event planning, research administration, business operations, process improvement, or office administration is preferred.
Technical Skills \& Expected Level of Proficiency
- Calendar Management \- Advanced
- Financial Administration \- Advanced
- Interpersonal Skills \- Advanced
- Meeting Coordination \- Advanced
- Office Procedures \- Advanced
- Oral and Written Communications \- Advanced
- Organizational Skills \- Advanced
- Report Writing \- Intermediate
*The core technical skills listed are most essential; additional technical skills may be required based on specific division or department needs.*
On call or non\-standard work hour requirements
- No regular on\-call requirement is anticipated. Occasional evening, early morning, or non\-standard hours may be required to support major DSAI events, advisory board or committee meetings, external partner meetings, program deadlines, or other time\-sensitive institute priorities.
Classified Title: Administrative Specialist
Role/Level/Range: ATP/03/PC
Starting Salary Range: $55,145 \- $96,760 Annually (Commensurate w/exp.)
Employee group: Full Time
Schedule: M\-F, 37\.5 hrs wkly
FLSA Status: Exempt
Location: Hybrid/Mount Washington Campus
Department name: DSAI Institute
Personnel area: Whiting School of Engineering
*Total Rewards*
The referenced base salary range represents the low and high end of Johns Hopkins University’s salary range for this position. Not all candidates will be eligible for the upper end of the salary range. Exact salary will ultimately depend on multiple factors, which may include the successful candidate's geographic location, skills, work experience, market conditions, education/training and other qualifications. Johns Hopkins offers a total rewards package that supports our employees' health, life, career and retirement. More information can be found here: https://hr.jhu.edu/benefits\-worklife/.
*Education and Experience Equivalency*
Please refer to the job description above to see which forms of equivalency are permitted for this position. If permitted, equivalencies will follow these guidelines: JHU Equivalency Formula: 30 undergraduate degree credits (semester hours) or 18 graduate degree credits may substitute for one year of experience. Additional related experience may substitute for required education on the same basis. For jobs where equivalency is permitted, up to two years of non\-related college course work may be applied towards the total minimum education/experience required for the respective job.
*Applicants Completing Studies*
Applicants who do not meet the posted requirements but are completing their final academic semester/quarter will be considered eligible for employment and may be asked to provide additional information confirming their academic completion date.
*Background Checks*
The successful candidate(s) for this position will be subject to a pre\-employment background check. Johns Hopkins is committed to hiring individuals with a justice\-involved background, consistent with applicable policies and current practice. A prior criminal history does not automatically preclude candidates from employment at Johns Hopkins University. In accordance with applicable law, the university will review, on an individual basis, the date of a candidate's conviction, the nature of the conviction and how the conviction relates to an essential job\-related qualification or function.
*Diversity and Inclusion*
The Johns Hopkins University values diversity, equity and inclusion and advances these through our key strategic framework, the JHU Roadmap on Diversity and Inclusion.
*Equal Opportunity Employer*
All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
*EEO is the Law*
https://www.eeoc.gov/sites/default/files/2023\-06/22\-088\_EEOC\_KnowYourRights6\.12ScreenRdr.pdf
*Accommodation Information*
If you are interested in applying for employment with The Johns Hopkins University and require special assistance or accommodation during any part of the pre\-employment process, please contact the Talent Acquisition Office at [email protected]. For TTY users, call via Maryland Relay or dial 711\. For more information about workplace accommodations or accessibility at Johns Hopkins University, please visit: https://accessibility.jhu.edu/.
*Vaccine Requirements*
Johns Hopkins University requires all faculty, staff, and students to receive the seasonal flu vaccine. Exceptions to the flu vaccine requirements may be provided to individuals for religious beliefs or medical reasons. Requests for an exception must be submitted to the JHU vaccination registry.
*The following additional provisions may apply, depending upon campus. Your recruiter will advise accordingly.*
The pre\-employment physical for positions in clinical areas, laboratories, working with research subjects, or involving community contact requires documentation of immune status against Rubella (German measles), Rubeola (Measles), Mumps, Varicella (chickenpox), Hepatitis B and documentation of having received the Tdap (Tetanus, diphtheria, pertussis) vaccination. This may include documentation of having two (2\) MMR vaccines; two (2\) Varicella vaccines; or antibody status to these diseases from laboratory testing. Blood tests for immunities to these diseases are ordinarily included in the pre\-employment physical exam except for those employees who provide results of blood tests or immunization documentation from their own health care providers. Any vaccinations required for these diseases will be given at no cost in our Occupational Health office.
Salary Context
This $55K-$96K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $175K across 2162 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Johns Hopkins University, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $214,900 based on 6,420 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($75K) sits 65% below the category median. Disclosed range: $55K to $96K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Johns Hopkins University AI Hiring
Johns Hopkins University has 5 open AI roles right now. They're hiring across AI/ML Engineer, AI Software Engineer. Positions span Baltimore, MD, US, Washington, DC, US. Compensation range: $76K - $96K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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