Interested in this AI/ML Engineer role at American Institutes for Research?
Apply Now →About This Role
AIR is seeking a Project Director to provide strategic, intellectual, and operational leadership for the organization’s flagship AI Century Study. The AI Century Study is a 100\-year national research effort to understand how artificial intelligence (AI) is reshaping human development and society. Unlike short\-term or one\-time studies, the AI Century Study will return to participating families at regular intervals for repeated data collection, allowing researchers to observe how AI\-related experiences and outcomes evolve across key life stages. This long\-term design will help identify patterns that are difficult to detect in snapshots—and clarify how impacts differ by context, including varying access to technology and resources. The ideal candidate will: bring a strong track record leading complex, multi\-year research initiatives; have demonstrated results with cultivating cross\-sector partnerships that generate rigorous, accessible, longitudinal evidence; and hold intellectual curiosity for the main question driving the study AIR is seeking a Project Director to provide strategic, intellectual, and operational leadership for the organization’s flagship (“*How does the age of AI change the human condition?*”).
The Project Director will help shape the vision and lead the execution and evolution of the AI Century Study, serving as both scientific steward and strategic leader. This role is responsible for guiding interdisciplinary teams, managing complex partnerships, and ensuring the study produces high\-quality evidence that informs policy, practice, and public understanding of AI’s long\-term impacts. The Project Director will work closely with AIR senior leadership, researchers across disciplines, external collaborators, and funders, and will represent the study publicly as a thought leader in AI and education research.
At AIR, we create impact through evidence that improves lives and systems. The AI Century Study is a cornerstone of AIR’s forward\-looking research agenda, addressing urgent questions about how AI is reshaping human development and society. The Project Director ensures that this work is human\-centered; scientifically rigorous and methodologically innovative; credible, transparent, and policy\-relevant; and designed for learning over time, not just one\-off findings.
This position has the flexibility to work remotely within the United States (U.S.) or from one of AIR’s U.S. office locations. This does not include U.S. territories.
About AIR:
Founded in 1946 and headquartered in Arlington, Virginia, the American Institutes for Research (AIR) is a nonpartisan, not\-for\-profit organization that conducts behavioral and social science research and delivers technical assistance to address some of the most pressing challenges in the United States and globally. Mission\-focused and evidence\-driven, AIR applies rigorous research and technical expertise to close gaps in opportunity and access, improving lives across communities and systems.
Responsibilities:
The responsibilities for the position include:
Strategic and Scientific Leadership
- Contribute to and support the refinement of the strategic vision for the AI Century Study, ensuring alignment with AIR’s mission.
- Provide intellectual leadership on research questions, study design, and the evolution of the study over time.
- Integrate qualitative, quantitative, longitudinal, and design\-informed research methods.
- Guide synthesis of findings into clear, compelling insights for diverse technical and non\-technical audiences.
Research Execution and Quality Assurance
- Lead the full research lifecycle, including data collection, governance, ethics, privacy, and security across all study components.
- Ensure high standards for research quality, transparency, and reproducibility.
- Apply adaptive learning, reflection, and iterative improvement as the study evolves.
Partnership and Stakeholder Engagement
- Develop strategic relationships with funders, academic collaborators, school systems, policymakers, and technology stakeholders.
- Serve as a key point of contact for major external partners and funders.
- Lead collaborative research activities such as listening sessions, convenings, and co\-design or co\-learning workshops.
- Identify and pursue opportunities to expand the study’s reach, sustainability, and influence through partnerships, co\-funding, and aligned initiatives.
Communication and Thought Leadership
- Significantly contribute to dissemination and knowledge\-translation strategies, including the development of reports, briefs, convenings, and public\-facing products.
- Represent the AI Century Study and AIR in national forums, media, and professional communities.
- Translate complex and longitudinal findings into accessible, actionable narratives that inform policy and practice.
- Program and Team Leadership Lead, supervise, and mentor a multidisciplinary team of researchers, analysts, designers, and communications staff.
- Foster a collaborative, inclusive, and high\-performing team culture grounded in rigor, curiosity, and continuous learning.
- Coordinate across AIR divisions and technical areas to ensure coherence, alignment, and effective use of institutional expertise.
Qualifications:
Education, Knowledge, and Experience
- PhD with a minimum of 7 years of relevant experience, or Master’s degree with a minimum of 11 years of experience in one or more of the following areas: human development, health, workforce development, education, or learning sciences; social science research, evaluation, or longitudinal study leadership; technology policy, data science, or applied research related to digital or AI\-enabled systems.
- Proven record of directing large\-scale, multi\-year research or evaluation projects, including responsibility for study design, implementation, and learning over time.
- At least 5 years of experience managing, or contributing to complex research initiatives, partnerships, or portfolios spanning multiple organizations or sectors (e.g., nonprofit, government, academia, philanthropy, technology partners).
- Demonstrated success building and sustaining partnerships across sectors and disciplines to support long\-term research and learning agendas.
- Professional reputation and network in fields relevant to the AI Century Study.
- Direct experience translating research and evidence into policy\- or practice\-relevant insights for technical and non\-technical audiences.
- Experience with longitudinal, cohort\-based, or life\-course\-oriented studies.
- Comfort engaging with both technical and non\-technical stakeholders, including policymakers, practitioners, and the public.
- Experience across domains of human development, health, education, workforce, and technology.
- Experience at the intersection of AI and human development Background in human\-centered research approaches.
Skills
- Intellectual curiosity for the main study question – *“How does the age of AI change the human condition?”*
- Systems\-oriented thinker with a deep understanding of systems change; able to see connections across research, policy, technology, and human experience.
- Highly organized and adaptable, able to manage multiple priorities and navigate ambiguity in dynamic, evolving research environments.
- Excellent communicator and storyteller who can translate complex, longitudinal findings into clear, actionable insights for varied audiences.
- Strong leader and people manager with a demonstrated commitment to mentorship, collaboration, and staff development within interdisciplinary teams.
Disclosures: Applicants must be currently authorized to work in the U.S. on a full\-time basis. Employment\-based visa sponsorship (including H\-1B sponsorship) is not available for this position. Depending on project work, qualified candidates may need to meet certain residency requirements.
American Institutes for Research is an equal employment opportunity/affirmative action employer. All qualified applicants will receive consideration for employment without discrimination on the basis of any characteristic protected by applicable federal, state or local law, including, but not limited to, actual or perceived race (including traits historically associated with race, such as hair texture, hair type, and protective hairstyles such as braid, locks, and twists), creed, color, religion, alienage or national origin, ancestry, citizenship status, age, physical or mental disability, medical condition (e.g., cancer), sex, gender, gender identity or expression (including transgender status), sexual orientation, marital status, civil union status, pregnancy, childbirth or related medical conditions, genetic information, or military or veteran status. AIR adheres to strict child safeguarding principles. All selected candidates will be expected to adhere to these standards and principles and will therefore undergo reference and background checks. AIR maintains a drug\-free work environment.
ACCESSIBILITY NOTICE: If you need a reasonable accommodation for any part of the employment process due to a physical or mental disability, please send an email to Taliba Boone at [email protected] call 202\.403\.5000\.
Fraudulent Job Scams Warning \& Disclaimer: AIR is aware of individuals falsely presenting themselves as AIR representatives. Fraudulent job scams seek to extract sensitive information or money from victims. To protect yourself, please be aware that AIR recruitment will only email you from an “@air.org” domain. Please take extra caution while examining the email address, for example [email protected] is correct and [email protected] is not a legitimate AIR email address. If you are unsure of the legitimacy of a communication you have received, please reach out to [email protected]. If you see a job scam, or lose money to one, report it to the Federal Trade Commission (FTC) at ReportFraud.ftc.gov. You can also report it to your state attorney general. Find out more about how to avoid scams atftc.gov/scams.
\#LI\-MP1 \#LI\-Remote
AIR’s Total Rewards Program, is designed to reward our staff competitively and motivate them to achieve our critical mission. This position offers the anticipated annual salary as listed. Salary offers are made based on internal equity within the institution and external equity with competitive markets. Please note this is the annual salary range for candidates that are based in the United States.
Anticipated Annual Salary Range
$165,000 \- $200,000 USD
Salary Context
This $165K-$200K range is above the median for AI/ML Engineer roles in our dataset (median: $180K across 1841 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 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At American Institutes for Research, 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 $218,750 based on 3,817 positions with disclosed compensation. Director-level AI roles across all categories have a median of $272,150. This role's midpoint ($182K) sits 17% below the category median. Disclosed range: $165K to $200K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
American Institutes for Research AI Hiring
American Institutes for Research has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Remote, US. Compensation range: $200K - $200K.
Remote Work Context
Remote AI roles pay a median of $185,334 across 717 positions. About 14% of all AI roles offer remote work.
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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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