Interested in this AI/ML Engineer role at US National Geospatial-Intelligence Agency?
Apply Now →About This Role
Summary
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Data Analysts combine mission and business analytics knowledge and a consultative approach to prepare reports, briefings, and communicate recommendations to enable stakeholder decision making. Data analysts identify, collect, structure, and evaluate data from various sources to meet analytic needs and prepare data for analysis using a range of data and visualization tools in alignment with data go
Learn more about this agency
This job is open to
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### The public
U.S. Citizens, Nationals or those who owe allegiance to the U.S.
### Clarification from the agency
External Applicants Only
Duties
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ADDITIONAL INFORMATION: The Office of the Chief Information Officer serves as NGA's central technology authority, providing enterprise\-wide leadership and integration across all information systems that power the agency's geospatial intelligence capabilities. OCIO establishes the technological foundation on which NGA accomplishes its mission by integrating cutting\-edge technologies that enable NGA to maintain its position as the world leader in geospatial intelligence and GEOINT AI. Through its unified C\-Suite \- the Chief Enterprise Architect, Chief Engineer, Chief Information Security Officer, Chief Data Officer, Chief Artificial Intelligence Officer, and Chief Technology Officer \- OCIO provides strategic direction, governance, and integration that ensures the agency is building the right things, the right way, together. OCIO drives IT policy and direction for NGA, architecting tomorrow's intelligence advantage today.
The Office of Artificial Intelligence (TI) serves as NGA's center of excellence for artificial intelligence and machine learning technologies, driving the Agency's AI strategy, governance, and implementation across all mission areas. TI assists the Chief Artificial Intelligence Officer (CAIO) in their duties to coordinate artificial intelligence across NGA, developing enterprise AI capabilities, and ensuring responsible and ethical AI development and deployment throughout the Agency. The office leads AI policy development, standards creation, and governance frameworks that enable NGA to harness AI's transformative potential while managing associated risks.
Requirements
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### Conditions of employment
- US Citizenship is required.
- Designated or Random Drug Testing required.
- Security Investigation
SPECIAL INFO:
As a condition of employment at NGA, persons being considered for employment must meet NGA fitness for employment standards.
- U.S. Citizenship
\- Security Clearance \- Top Secret /Sensitive Compartmented Information (SCI)
- Polygraph \& Drug Test
- Direct Deposit
- Trial Period during which we will evaluate your fitness and whether your continued employment advances the public interest. We may consider: performance conduct; needs and interests of the agency; and whether your continued employment would advance organizational goals of the agency or the Government and the efficiency of the Federal service
SPECIAL REQUIREMENTS:
You must be able to obtain and retain a Top Secret security clearance with access to SCI. In addition, you are subject to a Counterintelligence Polygraph examination in order to maintain access to Top Secret information. All employees are subject to a periodic examination on a random basis in order to determine continued eligibility. Refusal to take the examination may result in denial of access to Top Secret information, SAP, or unescorted access to SCIFs.
Employees with SCI access and who are under NGA cognizance are required to submit a Security Financial Disclosure Report, SF\-714, on an annual basis in order to determine continued eligibility. Failure to comply may negatively impact continued access to Top Secret information, Information Systems, SAP, or unescorted access to SCIFs.
NGA utilizes all processes and procedures of the Defense Civilian Intelligence Personnel System (DCIPS). Non\-executive NGA employees are assigned to five distinct pay bands based on the type and scope of work performed. The employee's base salary is established within their assigned pay band based on their unique qualifications. A performance pay process is conducted each year to determine a potential base pay salary increase and/or bonus. An employee's annual performance evaluation is a key factor in the performance pay process.
This position is a DCIPS position in the Excepted Service under 10 U.S.C. 1601\. DoD Components with DCIPS positions apply Veterans' Preference to preference eligible candidates as defined by Section 2108 of Title 5 USC, in accordance with the procedures provided in DoD Instruction 1400\.25, Volume 2005, DCIPS Employment and Placement. If you are an external applicant claiming veterans' preference, as defined by Section 2108 of Title 5 U.S.C., you must self\-identify your eligibility.
### Qualifications
MANDATORY QUALIFICATION CRITERIA: For this particular job, applicants must meet all competencies reflected under the Mandatory Qualification Criteria to include education (if required). Online resumes must demonstrate qualification by providing specific examples and associated results, in response to the announcement's mandatory criteria specified in this vacancy announcement:
At least 10 years of progressively responsible experience in artificial intelligence, machine learning, computer science, data science, software engineering, or related technical fields;
Demonstrated experience evaluating, comparing, and assessing AI systems, platforms, models, and services for mission suitability, technical maturity, scalability, interoperability, security, and operational value;
Demonstrated experience leading the implementation, integration, or scaling of AI and automation capabilities in complex enterprise, defense, intelligence, or national security environments;
Excellent collaboration, oral and written communication skills, including the ability to produce clear, technically credible written products and recommendations for senior leaders, technical teams, and external partners;
Deep understanding of modern AI technologies, methodologies, and implementation patterns, including large language models, retrieval\-augmented generation, AI agents, multimodal models, model evaluation, benchmarking, and AI security.
EDUCATION REQUIREMENT: A. Education: Bachelor's degree from an accredited college or university in Data Analytics, Business Intelligence, Mathematics, Statistics, Actuarial Science, Computer Science, Engineering, Information Design, Operations Research, Finance, Information Technology, or a related field. \-OR\- B. Combination of Education and Experience: A minimum of 24 semester (36 quarter) hours of coursework in any area listed in option A, plus experience that requires the application of tools and algorithms to identify trends and patterns in data, or in a related area that demonstrates the ability to successfully perform the duties associated with this work. As a rule, every 30 semester (45 quarter) hours of coursework is equivalent to one year of experience. Candidates should show that their combination of education and experience totals 4 years.
DESIRABLE QUALIFICATION CRITERIA: In addition to the mandatory qualifications, experience in the following is desired:
At least 10 years of military service or experience working with or in direct support of military units, particularly in intelligence, cyber, operational planning, geospatial, or related mission areas;
Experience with the IC Foundational AI Stack and related enterprise AI services;
Experience supporting AI\-related acquisition, contractor oversight, or technical program execution, including service as a Contracting Officer's Representative (COR);
Experience reading and assessing technical architecture documents, model documentation, implementation plans, and system dependencies in support of enterprise adoption decisions;
Demonstrated experience designing, building, or scaling AI and automation capabilities to improve mission effectiveness, efficiency, or operational outcomes.
### Additional information
Candidates should be committed to improving the efficiency of the Federal government, passionate about the ideals of our American republic, and committed to upholding the rule of law and the United States Constitution.
Benefits
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Review our benefits
How you will be evaluated
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You will be evaluated for this job based on how well you meet the qualifications above.
Applicants are not required to submit a cover letter for employment consideration with the National Geospatial\-Intelligence Agency. However, a cover letter is recommended. Applicants will have the option to attach a cover letter in the Qualifications \- Attachments step of the online application.
APPLICANT EVALUATION PROCESS:
1\) All applicants will be evaluated using the Mandatory Qualification Criteria,
2\) Qualified applicants will then be evaluated by an expert or panel of experts using a combination of qualification criteria to determine the best\-qualified candidates,
3\) Best\-qualified applicants may then be further evaluated through an interview process.
Military retiree applicants, if selected, may be impacted by the 180\-day appointment restrictions of DODI 1402\.01\. HD personnel will provide additional information if applicable.
Applicants are encouraged to carefully review the Assignment Description, Additional Information Provided By the Selecting Official, and the Qualification Requirements; and then construct their resumes to highlight their most relevant and significant experience and education for this job opportunity. This description should include examples that detail the level and complexity of the performed work. Applicants are encouraged to provide any education or degree information referenced in the announcement that is relevant. If education is listed as a mandatory requirement, only degrees obtained from an institution accredited by an accrediting organization recognized by the Secretary, US Department of Education will be accepted. You must use the NGA resume builder and limit your resume to 2 pages.
In accordance with section 9902(h) of title 5, United States Code, annuitants reemployed in the Department of Defense shall receive full annuity and salary upon appointment. They shall not be eligible for retirement contributions, participation in the Thrift Savings Plan, or a supplemental or re\-determined annuity for the reemployment period. Discontinued service retirement annuitants (i.e., retired under section 8336(d)(1\) or 8414(b)(1\)(A) of title 5, United States Code) appointed to the Department of Defense may elect to be subject to retirement provisions of the new appointment as appropriate. (See DoD Instruction 1400\.25, Volume 300\). Reemployed annuitants must meet additional selection criteria as outlined in the DODI 1400\.25, v300\.
All candidates will be considered without regard to race, color, religion, sex, national origin, age, marital status, disability, or sexual orientation.
NGA provides reasonable accommodations to applicants with disabilities. Applications will only be accepted online. If you need a reasonable accommodation for any part of the application and hiring process, please notify us at [email protected]. The decision on granting reasonable accommodation will be on a case\-by\-case basis.
Required Documents
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None
### If you are relying on your education to meet qualification requirements:
Education must be accredited by an accrediting institution recognized by the U.S. Department of Education in order for it to be credited towards qualifications. Therefore, provide only the attendance and/or degrees from schools accredited by accrediting institutions recognized by the U.S. Department of Education.
Failure to provide all of the required information as stated in this vacancy announcement may result in an ineligible rating or may affect the overall rating.
How to Apply
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Application submission involves applying using NGA's online application process at NGA Careers Portal. Additional information concerning NGA's hiring process can be found by visiting NGA Hiring Process.
All announcements close at 11:59PM EDT on the closing date listed. Be sure to complete and submit your application by that time in order to be considered.
ONLY ELECTRONIC SUBMISSIONS WILL BE ACCEPTED.
Both applicants for employment and current employees of NGA are entitled to request religious accommodations from generally applicable employment\-related rules and requirements, so long as the accommodation requested would not result in an undue hardship to the conduct of NGA's business.
You can apply for the job opening at https://careers.nga.mil/psp/CAREERS/EMPLOYEE/HRMS/c/HRS\_HRAM\_FL.HRS\_CG\_SEARCH\_FL.GBL?Page\=HRS\_APP\_JBPST\_FL\&Action\=U\&FOCUS\=Applicant\&SiteId\=1\&JobOpeningId\=20260271\&PostingSeq\=2
### Agency contact information
Recruitment
Phone
571\-557\-1999
Address
*NATIONAL GEOSPATIAL\-INTELLIGENCE AGENCY*
*Mailstop: S44\-HDR*
*7500 GEOINT Drive*
*Springfield, VA 22150*
*US*### Next steps
After visiting the NGA Careers Portal and applying via NGA's online application process, applicants can follow their status via that same NGA online application functionality. Several other topics relating to what is involved in the hiring process and how long it takes can be found by visiting the NGA Hiring Process.
Overview
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Accepting applications
Location
Many vacancies in the following location:
Springfield, VA
1 vacancy
No matching locations found.
Work site options
Telework eligible
No
Relocation expenses reimbursed
No
Salary
$169,279 \- $197,200 per year
Pay scale \& grade
IA 05
Promotion potential
5
Learn more about pay scale and grade
Pay scale and grade determines the salary of the job.
Work schedule
Full\-time \- Full Time
Travel Required
Not required
Appointment type
Permanent \- This is a permanent position.
Occupations and job series
- 1501 General Mathematics And Statistics
Supervisory status
No
Federal service type
This job is in the Excepted Service
Drug test
Yes
Security clearance
Sensitive Compartmented Information
Announcement number
20260271
Control number
879303100
Salary Context
This $169K-$197K range is above the median 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 US National Geospatial-Intelligence Agency, 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 in Demand for This Role
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. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($183K) sits 15% below the category median. Disclosed range: $169K to $197K.
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.
US National Geospatial-Intelligence Agency AI Hiring
US National Geospatial-Intelligence Agency has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Springfield, VA, US. Compensation range: $197K - $197K.
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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