Interested in this AI/ML Engineer role at Ford Foundation?
Apply Now →About This Role
*Please submit both a resume and cover letter in order to be considered. The deadline to apply is July 6th, 2026\.*
ABOUT THE OPPORTUNITY
The Ford Foundation seeks a two\-year Technology Fellow for AI and Philanthropy. This internally\-facing position will focus on cross\-programmatic learning and advisory support. The AI Tech Fellow will support Foundation staff in building and adapting internal frameworks for evaluating AI use in ways that prioritize mission and strategy and address ethical, sociotechnical, and operational considerations.
Reporting to the Director, Technology and Society, they will be responsible for designing and curating practical, hands\-on training, workshops, and learning sessions for Foundation staff to build practical familiarity with AI tools and practices and help staff critically assess their value and efficacy. Additionally, they will curate sociotechnical conversations exploring how philanthropy and the nonprofit sector more broadly are experimenting with AI in ways that respect and advance mission, privacy, safety, and equity, and create accessible documentation and guides on AI experimentation for Foundation staff.
The AI Tech Fellow will also be responsible for research and field engagement. They will monitor emerging, global AI developments relevant to the Foundation's program strategies and operations, providing timely briefings and analysis to program teams. They will conduct landscape research on AI initiatives in the philanthropy and social justice sectors, build relationships with AI researchers, practitioners, and organizations working on mission\-enabling AI development, and identify and connect grantees and partners who are thoughtfully experimenting with the use of AI and related technologies in their work.
ABOUT THE TECH FELLOW PROGRAM
The Ford Technology Fellows Program is designed to increase sociotechnical (understanding how technology and social systems shape each other) capacity within the Foundation, explore emerging ideas and practices at the intersection of technology and social change, and build new relationships and networks. The Technology Fellows program is administered by Ford’s Technology and Society Program, which works globally to ensure that the internet and digital technologies are increasingly equitable and are designed and governed to advance social and economic justice, particularly for those experiencing persistent discrimination. This role does not include IT and administration responsibilities, however, the Tech Fellow will partner with members of the Information Technology team to collaborate on common and overlapping initiatives and facilitate alignment between our internal and external strategies.
Technology Fellows play a strategic advisory role within the Foundation as well as provide practical technical expertise to foundation staff and grantees; identify emerging opportunities and challenges; help develop networks and communities of social justice mission\-driven technology experts; and enrich the diverse perspectives of the Foundation’s program experts.
HOW YOU WILL CONTRIBUTE
The Technology Fellowship Program has three overarching goals:
- Enrich perspectives within the foundation by adding a socio\-technical lens
- Increase technical capacity throughout the foundation’s areas of work
- Generate novel, innovative ideas and build new relationships and networks
Innovative Strategic Advising:
- Help Foundation staff examine the role of technology in advancing organizational objectives
- Inform development of technology strategies within program and/or operations areas, and conducting landscape research
- Design and curate hands\-on trainings, workshops, and learning sessions for Foundation staff to build practical familiarity with AI tools and practices and help staff critically assess their value and efficacy
- Develop accessible documentation and guides on mission aligned AI experimentation for Foundation staff
- Serve as an internal technology advisory resource on how philanthropy and the nonprofit sector are experimenting with AI in ways that respect and advance mission
- In collaboration with the Tech and Society team, develop learning sessions and training for foundation staff about the intersections of social justice and technology
- Support the Technology and Society Director on other Foundation priorities
WHAT YOU WILL NEED
- Minimum 7 years working within public interest, government, civil society, or commercial technology sectors.
- Baccalaureate degree in related field or relevant and equivalent experience.
- Demonstrated sociotechnical expertise in artificial intelligence and related technologies, including understanding the practical applications of machine learning systems, generative AI, and their societal implications.
- Ability to critically evaluate and assess the practical application of AI and related technologies within social change organizations, particularly regarding usefulness, effectiveness, security, and potential social and environmental impact.
- Experience in understanding the technical needs of mission driven organizations, and collaboratively designing technical solutions to advance organizational mission and strategy.
- Experience designing, implementing, or supporting AI applications and tools in a complex, global setting.
- Strong strategic communication skills, including the ability to collaborate with and articulate the potential roles and importance of technology to diverse audiences.
- Experience working with diverse individuals across civil society, government, and the private sector.
- Familiarity with information and communication technologies specifically designed to serve the public interest.
- Ability to evaluate existing and emerging technologies for usefulness, effectiveness, security risks, and potential alignment with Ford’s programmatic work.
- Excellent analytical, writing, oral presentation, information curation, and interpersonal skills.
- Ability to handle confidential issues with appropriate discretion.
- Action\-oriented, disciplined, and self\-motivated; highly comfortable working both independently and collaboratively with diverse teams.
- Demonstrates humility, a capacity for self\-reflection, and a sense of humor.
- Ways of working and engaging that aligns with the Foundation’s mission, core values and commitment to creating a culture of excellence.
- Willingness to work in New York City.
HELPFUL BUT NOT REQUIRED
- Experience in change management and organizational transition is preferred.
- Familiarity with the regional context and cultures, including geopolitical landscape, in which Ford works.
PHYSICAL DEMANDS
This position is primarily a sedentary role. However, the person in this position may need to occasionally move about inside the office to liaise with internal staff, access files, office machinery and a copy machine/printer.
The Ford Foundation is committed to providing access, equal opportunity and reasonable accommodation for individuals with disabilities in employment, its programs, and operations. As part of this commitment, the Foundation will ensure that persons with disabilities are provided reasonable accommodations. If a reasonable accommodation is needed to participate in the job application process, please contact [email protected]*.*
SALARY: The Ford Foundation is committed to salary transparency. The minimum salary for this position is $166,000, and the maximum is $170,000\. It is not typical for an individual to be hired at or near the top of this range. A candidate’s relevant experience and our commitment to internal equity determine the final offer. We review global compensation regularly to ensure market competitiveness and equity. The hiring range for this position has been carefully crafted to align with the market.
LOCATION: This position is based in the foundation’s New York office. We operate in a hybrid model and require staff to be in the office three days per week.
WORK AUTHORIZATION: This position is not eligible for employment visa sponsorship now or in the future. All candidates must be legally authorized to work in the United States.
EMPLOYMENT TYPE: This is a term\-limited position with a two\-year contract.
WORKING AT FORD
- Commitment to creating a culture where everyone feels respected
- A hybrid working model and flexible work arrangement policies offer colleagues the opportunity to engage in meaningful ways and the space to maintain a healthy work\-life balance
- Professional development and ample opportunities to build your expertise and expand your network
- Comprehensive benefits package designed for your well\-being and work\-life needs, including medical, dental, and vision benefits effective on your first day
- Generous time off, including personal, vacation, sick, extended holiday time off, and wellness days
- Generous parental leave policy, including birth, surrogacy, adoptive, foster parents, and resources for backup child and elder care that support our colleagues’ ability to attend to family responsibilities
- Comprehensive retirement benefits options (with employee and employer contributions of up to 13%), allowing you to invest in your financial future with confidence
*Equal employment opportunity and having a diverse staff are fundamental principles at The Ford Foundation, where employment and promotional opportunities are based upon individual capabilities and qualifications without regard to race, color, religion, gender, pregnancy, sexual* *orientation/affectional* *preference, age, national origin, marital status, citizenship, disability, veteran status or any other protected characteristic as established under law. T**he Ford Foundation does not discriminate against formerly incarcerated individuals.*
Salary Context
This $166K-$170K 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
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 Ford Foundation, 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 $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 ($168K) sits 7% below the category median. Disclosed range: $166K to $170K.
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.
Ford Foundation AI Hiring
Ford Foundation has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in New York, NY, US. Compensation range: $170K - $170K.
Location Context
AI roles in New York pay a median of $211,000 across 2,643 tracked positions. That's 5% above the national 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
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