Data Science - Technical

$106K - $214K Chandler, AZ, US Mid Level AI/ML Engineer

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Skills & Technologies

AwsDemandtoolsTableau

About This Role

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Summary

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The Department of Homeland Security (DHS) is recruiting professionals to support a range of technical roles in Cybersecurity Data Science, including Data Scientist, Data Engineers, Artificial Intelligence (AI) Specialist, AI Operations Analyst, Data Modeler, Data Security Officer and Operations Research Analyst. All positions are in the DHS Cybersecurity Service.

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.

Duties

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There are a variety of Cybersecurity Data Science opportunities across the Department, including supporting several specialized programs at the DHS Office of Strategy, Policy, and Plans (PLCY), the Cybersecurity and Infrastructure Security Agency (CISA), the DHS Office of the Chief Information Officer (OCIO), the Federal Emergency Management Agency (FEMA), the U.S. Immigration and Customs Enforcement Agency (ICE) and the U.S. Secret Service. As a DHS Cybersecurity Service employee in the Technical Career Track, you will continually maintain and share your Cybersecurity Data Science expertise to perform a range of critical, complex, routine and non\-routine tasks, including:

  • Applying knowledge of essential cybersecurity policies to data management to develop data standards, policies, and procedures to facilitate and implement data mining and data warehousing programs to collect, clean, convert and standardize complex data for analysis.
  • Conducting hypothesis testing using statistical processes applying quantitative techniques (e.g., descriptive and inferential statistics, sampling, experimental design) to assess the validity of source data and develop strategic insights from large data sets.
  • Proactively collaborating with systems analysts, engineers, and programmers to design applications integrating data from several disparate sources that is stored using different technologies to provide a unified view of the data.
  • Using a variety of tools, including Google Analytics, to monitor web data, log data, and threat data analytics, to provide a managed flow of relevant information based on cybersecurity mission requirements.
  • Analyzing and defining data requirements and specifications using various tools and methodologies (e.g., Statistical Package for Social Sciences \[SPSS], Statistical Analysis System \[SAS], R Analytics, Statistics and Data \[STATA]) to discover new patterns and behaviors providing DHS Headquarters (HQ) and/or Component stakeholders actionable recommendations.
  • Planning for anticipated changes in enterprise data capacity requirements and effectively allocating storage capacity in the design of new data management systems, technologies, and architectures.
  • Providing technical and nontechnical support to collect metrics and trending data using enterprise data management systems (e.g., SPLUNK) and cloud\-based systems (e.g., AWS).
  • Using data visualization tools (e.g., R, Tableau, Flare, Google Visualization Application Programming Interface \[API], RGIS) to design charts and exhibit graphic representations for the purposes of providing actionable recommendations to critical leadership officials and stakeholders.
  • Using various tools (e.g., SPSS, SAS, R, STATA) and methodologies for analyzing and interpreting complex data to discover new patterns and behaviors and provide usable information to decision makers and other users.
  • Designing and implementing data pipelines for the analysis of cyber data into systems.
  • Structuring, cleaning, enriching, and validating data in preparation for discovery and use.
  • Building and maintaining scalable database architecture and data processing systems.

Requirements

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### Conditions of employment

  • You must be a U.S. Citizen or national.
  • You must be 18 years of age.
  • Must be registered for the Selective Service (if you are a male).
  • Must be able to obtain and maintain a security clearance. Security clearance levels may vary.
  • Must be able to submit to a drug test and receive a negative result.
  • Must be able to comply with ethics and standards of conduct requirements, including completing any applicable financial disclosure.
  • May be required to serve a 3 year probationary period.

### Qualifications

This position is in the Technical Track across a range of career levels. Employees in this career track generally:

  • Have between 5\-15 years of cybersecurity work experience.
  • Range from experienced cybersecurity professionals who apply technical expertise and independent judgement to perform cybersecurity work \- to \- recognized Federal cybersecurity technical authorities with uncommon technical expertise who advise on cybersecurity challenged impacting DHS and the Nation.

DHS Cybersecurity Service employees with a technical capability in Cybersecurity Data Science will generally:

  • Examine data with the goal of providing new insight for the purposes of cybersecurity.
  • Design and implement custom algorithms, flow processes and layouts for complex, enterprise\-scale data sets used for modeling, data analytics, and research purposes.
  • Apply understanding of cybersecurity field to inform analytical methodologies and algorithms selected for implementation.
  • Design, build, implement, integrate, and maintain systems and tools for data trend and pattern analysis of cyber data.
  • Apply knowledge of statistics and mathematical theory to develop and integrate new and emerging technologies, such as machine learning and deep learning concepts and techniques.
  • Communicate insights gained to mission user.

DHS Cybersecurity Service employees start at career levels and salaries matching their experience and expertise. To learn more about DHS Cybersecurity Service career tracks and levels, visit our application portal.

This position is focused on Cybersecurity Data Science.

DHS Cybersecurity Service jobs are structured cybersecurity specializations \- called technical capabilities. To learn more about technical capabilities, visit our application portal.

### Education

Degrees are not required for jobs in the DHS Cybersecurity Service, but DHS is interested in your level of education and the topics you studied. As you submit initial application information, you will be asked questions about your education.

### Additional information

*Salary:* Listed salary ranges reflects typical starting salaries available to employees in most of the United States across applicable career levels. Within the provided range, average salaries vary for each career level.

Senior Cybersecurity Specialist: $106,700 \- $138,000

Staff Cybersecurity Specialist: $129,700 \- $163,000

Principal Cybersecurity Specialist: $154,600 \- $196,500

Senior Principal Cybersecurity Specialist: $170,600 \- $214,500

In some geographic areas, average starting salaries will be higher because of a local cybersecurity labor market supplement (e.g., metro Washington, D.C. \+10%).

Actual salaries of individual employees may be higher or lower than provided figures. For an overview of the salaries available in the DHS Cybersecurity Service, visit Resources.

*Benefits:* DHS Cybersecurity Service employees receive a range of federal employment benefits designed to support their professional and personal lives. To learn more about benefits, visit our application portal.

More information about the specific benefits available to you will be provided as you progress through the application process.

*Background Investigation:* To ensure the accomplishment of its mission, the Department of Homeland Security (DHS) requires each and every employee to be reliable and trustworthy. To meet those standards, all selected applicants must undergo and successfully complete a background investigation for a security clearance as a condition of placement in this position. This review includes financial issues such as delinquency in the payment of debts, child support and/or tax obligations, as well as certain criminal offenses and illegal use or possession of drugs.

Pursuant to Executive Order 12564 and DHS policy, DHS is committed to maintaining a drug\-free workplace and, therefore, conducts random and other drug testing of its employees in order to ensure a safe and healthy work environment. Headquarters personnel in safety\- or security\-sensitive positions are subject to random drug testing and all applicants tentatively selected for employment at DHS Headquarters are subject to drug testing resulting in a negative test result.

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

========

A career with the U.S. government provides employees with a comprehensive benefits package. As a federal employee, you and your family will have access to a range of benefits that are designed to make your federal career very rewarding. Opens in a new windowLearn more about federal benefits.

Eligibility for benefits depends on the type of position you hold and whether your position is full\-time, part\-time or intermittent. Contact the hiring agency for more information on the specific benefits offered.

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.

All DHS Cybersecurity Service (DHS\-CS) applicants participate in a multi\-phase assessment process, which varies by career track. For the Technical Career Track, applicants participate in a two\-phase assessment process:

  • You must successfully complete each phase to advance to the next phase.
  • The total time commitment for the two phases is approximately 4 hours (many applicants require less time!).
  • Before each phase, DHS will e\-mail you instructions and information to help you prepare.
  • Assessments are time sensitive, so monitor your e\-mail to ensure you have plenty of time to complete them prior to any deadlines.

PHASE I: ONLINE ASSESSMENTS* Un\-proctored \- Completed online within a prescribed period of time.

  • Includes two assessments: (1\) a work styles inventory that will take about 30 minutes to complete; (2\) a work simulation that you will have up to 2 hours to complete.
  • The two assessments take about 90 minutes (on average) to complete.
  • Requires a computer with audio (speakers or headphones) and a reliable internet connection.
  • No knowledge of DHS or cybersecurity is required for these assessments, which measure non\-technical capabilities that are important for professional success in the DHS\-CS. This includes how you communicate, analyze information, and collaborate with others:

+ The work styles inventory presents you with questions about your work\-related interests and preferences.

+ The work simulation presents you with realistic, work\-related scenarios and asks you to respond to them.

PHASE II: TECHNICAL CAPABILITY ASSESSMENT

  • Proctored \- must be scheduled in advance and completed at a designated assessment center within a prescribed period of time
  • There is a different assessment for each DHS\-CS technical capability (visit Jobs to learn more about the technical capabilities).
  • Most individuals only have a primary technical capability and complete only one Technical Capability Assessment, but in limited circumstances, you may complete a second Technical Capability Assessment.
  • You will have up to 2\.5 hours to complete each Technical Capability Assessment; each takes about 90 minutes (on average) to complete.
  • Assessments present realistic, work\-related cybersecurity scenarios and questions to assess technical skills.
  • Cybersecurity knowledge is assessed, but no knowledge of DHS is required.
  • Applicants who successfully complete Phase II will undergo a resume review to confirm required experience. More information will be provided to such applicants as they progress through the application process.

NOTE: Your resume must explicitly outline your cybersecurity experience

Your proctored assessment results are valid for a period of one year after completion and will be kept and used toward future positions for which you might apply that require the same assessments.

To learn about the assessment process for this Technical Track position, visit our portal and read the "Assessment Process" guide.

Required Documents

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  • Your resume. To help you prepare your resume before applying to the DHS Cybersecurity Service, visit our application portal and read the "Resume Tips" guide.
  • If you are requesting a reasonable accommodation to the online assessments, submit documentation to support your request, including the Reasonable Accommodation Request Form found here.
  • If you are a current or former political Schedule A, Schedule C, Non\-career SES or Presidential Appointee employee please submit a copy of your applicable SF\-50, along with a statement that provides the following information regarding your most recent political appointment:\- Position title\- Type of appointment (Schedule A, Schedule C, Non\-career SES, or Presidential Appointee)\- Agency\- Beginning and ending dates of appointment

How to Apply

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To apply for this position, you must complete the initial online questionnaire, required assessments, and submit the documentation specified in the Required Documents section below. The complete application package must be submitted by 11:59 PM (ET) on 06/27/2026 to receive consideration. The application process will follow the bullets outlined below.

  • To begin the application process, click the Apply Online button.
  • Answer the questions presented in the application and attach all necessary supporting documentation.
  • Click the Submit Application button prior to 11:59PM (ET) on the announcement closing date.
  • After submitting an online application, you will be notified whether or not you are required to take additional online assessments through the USA HIRE platform. This message will be delivered via email notification.
  • If you are asked to take the online assessments, you will be presented with a unique URL to access the USA Hire system. Access to USA Hire is granted through your USAJOBS login credentials.

Be sure to review all instructions prior to beginning online assessments. Note: set aside at least 3 hours to take these assessments; however, most applicants complete the assessments in less time. If you need to stop the assessments and continue at a later time, you can re\-use the URL sent to you via email and also found on the Additional Application Information page that can be located in the application record in your USAJOBS account.

*Reasonable Accommodation Requests:* If you believe you have a disability (i.e., physical or mental), covered by the Rehabilitation Act of 1973 as amended and Americans with Disabilities Act 1990 as amended, that would interfere with completing online assessments on the USA HIRE platform, you will be granted the opportunity to request a reasonable accommodation in your online application. Requests for Reasonable Accommodations for the USA Hire Competency Based Assessments and appropriate supporting documentation for Reasonable Accommodation must be received prior to starting the online assessments. Decisions on requests for Reasonable Accommodations are made on a case\-by\-case basis. If you meet the minimum qualifications of the position, after notification of the adjudication of your request, you will receive an email invitation to complete the online assessments. You must complete all assessments within 48 hours of receiving the URL to access the online assessments. To determine if you need a Reasonable Accommodation, please review the Procedures for Requesting a Reasonable Accommodation for online assessments here: http://help.usastaffing.gov/Apply/index.php?title\=Reasonable\_Accommodations\_for\_USA\_Hire.

### Agency contact information

DHS Cybersecurity Service Talent Team

Email

[email protected]

Address

*Cybersecurity Talent Management System*

*245 Murray Lane SW*

*Washington, DC 20528*

*US*### Next steps

The DHS Cybersecurity Service application process is designed to both prioritize fairness to all applicants and identify qualified candidates to join the DHS Cybersecurity Service. Successful applicants proceed through the following steps and will receive notifications as each step is completed: Submit Initial Information

  • Upload resume
  • Answer questions about your expertise and experience

Assessment \+ Interview

  • Complete multi\-phase assessment process
  • Interview with the team you might join

Tentative Job Offer \+ Background Investigation

  • Receive a tentative job offer, including your compensation and benefits package
  • Receive an invitation to start the background investigation process

Final Job Offer \+ Start Date

  • Receive a final job offer
  • Determine your start date

We will notify you by email after each of these steps has been completed. Your status will also be updated on USAJOBS throughout the process. To check your status, log on to your USAJOBS account, click on "Application Status," and then click "More Information."

Note: If you successfully complete the application process and receive a tentative DHS Cybersecurity Service job offer, applicable employment eligibility requirements, including those you must comply with throughout your appointment at DHS, will be communicated to you in writing.

Any offers of employment made pursuant to this announcement will be consistent with all applicable authorities, including Presidential Memoranda, Executive Orders, interpretive U. S. Office of Management and Budget (OMB) and U. S. Office of Personnel Management (OPM) guidance, and Office of Management and Budget plans and policies concerning hiring. These authorities are subject to change.

DHS uses e\-Verify, an Internet\-based system, to confirm the eligibility of all newly hired employees to work in the United States. Learn more about E\-Verify, including your rights and responsibilities.(http://www.uscis.gov/e\-verify).

To learn more about DHS Cybersecurity Service employment eligibility, visit our application portal.

Overview

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Accepting applications

Posted today · Apply by 06/27/26

Due by 11:59 p.m. ET on June 27, 2026

Location

Many vacancies in the following locations:

Chandler, AZ

Washington, DC

Pensacola, FL

Idaho Falls, ID

Stennis Space Center, MS

Arlington, VA

Springfield, VA

No matching locations found.

Work site options

Telework eligible

Yes—as determined by the agency policy.

Remote job

No

Relocation expenses reimbursed

No

Salary

$106,700 \- $214,500 per year

Range reflects typical low and high starting salaries available to employees in most of the U.S. See Additional information: Salary for more info.

Pay scale \& grade

DC 2

Promotion potential

None

Learn more about pay scale and grade

Pay scale and grade determines the salary of the job.

Work schedule

Full\-time

Travel Required

Occasional travel \- You may be expected to travel for this position about 1 to 5 days a month.

Appointment type

Permanent

Occupations and job series

  • 2227 Cybersecurity Data Science (For DHS use only)

Supervisory status

No

Federal service type

This job is in the Excepted Service

Represented by a union

No

Drug test

Yes

Security clearance

Top Secret

Position sensitivity and risk

Critical\-Sensitive (CS)/High Risk

Jobs require a background check and some require a security clearance. The type depends on the job.

Background check type

  • National security

Financial disclosure required

Yes

Some jobs require financial disclosure to identify conflicts of interests.

Announcement number

26\-12977164\-CBWQ

Control number

872847100

Salary Context

This $106K-$214K range is below the median for AI/ML Engineer roles in our dataset (median: $180K across 1937 roles with salary data).

View full AI/ML Engineer salary data →

Role Details

Title Data Science - Technical
Location Chandler, AZ, US
Category AI/ML Engineer
Experience Mid Level
Salary $106K - $214K
Remote No

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 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% of the market. At US DHS Headquarters, 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

Aws (31% of roles) Demandtools (1% of roles) Tableau (4% of roles)

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 $181,170 based on 12,692 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $165,000. This role's midpoint ($160K) sits 11% below the category median. Disclosed range: $106K to $214K.

Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.

US DHS Headquarters AI Hiring

US DHS Headquarters has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Chandler, AZ, US. Compensation range: $214K - $214K.

Location Context

Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.

The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.

Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. 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 Engineering Manager roles lead at $275,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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

Based on 12,692 roles with disclosed compensation, the median salary for AI/ML Engineer positions is $181,170. Actual compensation varies by seniority, location, and company stage.
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.
About 15% of the 3,823 AI roles we track offer remote work. Remote availability varies by company and seniority level, with senior and leadership roles more likely to offer location flexibility.
US DHS Headquarters is among the companies actively hiring for AI and ML talent. Check our company profiles for detailed breakdowns of open roles, salary ranges, and hiring trends.
Common next steps from AI/ML Engineer positions include ML Architect, AI Engineering Manager, Principal ML Engineer. Progression depends on whether you lean toward technical depth, people management, or product strategy.

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