Interested in this AI/ML Engineer role at International Rescue Committee?
Apply Now →About This Role
The International Rescue Committee (IRC) responds to the world's worst humanitarian crises, helping to restore health, safety, education, economic wellbeing, and power to people devastated by conflict and disaster. Founded in 1933 at the call of Albert Einstein, the IRC is one of the world's largest international humanitarian non\-governmental organizations (INGO), at work in more than 40 countries and 29 U.S. cities helping people to survive, reclaim control of their future and strengthen their communities. A force for humanity, IRC employees deliver lasting impact by restoring safety, dignity and hope to millions. If you're a solutions\-driven, passionate change\-maker, come join us in positively impacting the lives of millions of people world\-wide for a better future.
Background/IRC Summary:
The International Rescue Committee helps people whose lives and livelihoods are shattered by conflict and disaster to survive, recover, and gain control of their future. Founded in 1933 at the request of Albert Einstein, the IRC works with people forced to flee from war, conflict and disaster and the host communities that support them, as well as with those who remain within their homes and communities. At work today in over 40 countries and 22 U.S. cities, we restore safety, dignity and hope to millions who are uprooted and struggling to endure.
The IT department provides end\-to\-end solutions for the organization including application development \& integration, system deployment, user experience and change management, quality assurance \& testing, and overall Project Management in an effort to help the organization determine and implement the best solutions for its business needs.
Job Overview/Summary:
This is a rare opportunity to sit at the center of one of the most consequential applications of AI in the social sector. As the IRC's AI Program Manager, you will help shape how a global humanitarian organization — operating in over 40 countries — harnesses artificial intelligence to improve outcomes for some of the world's most vulnerable people. This is not a role managing technology for its own sake; it is a role where smart, responsible AI adoption can directly accelerate impact at scale.
You will lead and coordinate the IRC's most important AI initiatives: driving enterprise AI projects from concept to delivery, ensuring that AI tools adopted across the organization are evaluated rigorously and responsibly, and coordinating the cross\-functional teams working to embed AI into how the IRC operates. You will work at the intersection of technology, program delivery, and organizational change — partnering with senior leaders, technical experts, and frontline staff across the globe.
The right candidate is a fast\-moving, proactive problem\-solver who thrives in ambiguity, brings structure to complex and evolving landscapes, and is energized by the challenge of building something new in an environment where the stakes are high and the work is genuinely meaningful.
This role reports to the AI Governance and Transformation Lead, and works in close partnership with Director, IT Project and Portfolio Management, AI project leads, senior sponsors, and a broad community of practice across the organization.
Major Responsibilities:
AI Governance (60%)
The IRC is committed to adopting AI responsibly. As part of this, the organization has established a structured review process for AI use cases that carry potential high risks — whether related to data privacy, security, bias, or ethical considerations. As coordinator of this process, you will:
- Manage the intake and documentation of AI use cases and tools flagged for high\-risk review.
- Assign cases to appropriate domain reviewers (e.g., legal, security, data protection, ethics) and coordinate their timely completion.
- Maintain templates, trackers, and a full audit trail of all reviewed use cases and decisions.
- Communicate clearly with requestors on process, status, and outcomes.
- Draft and maintain guidance documentation, publishing decisions and resources to the IRC's internal staff portal.
- Prepare agendas, materials, and logistics for review panel meetings.
- Support the implementation of IRC’s enterprise AI policy, building out the necessary tools and processes in close collaboration with others.
Enterprise AI Project Management (40%)
Lead project management for high\-priority, organization\-wide AI initiatives. Responsibilities include:
- Developing and maintaining detailed project plans, work breakdown structures, risk registers, and terms of reference.
- Facilitating scrum, sprint planning, and retrospective meetings; driving delivery against milestones.
- Designing and executing testing, rollout, and change management plans in partnership with cross\-functional stakeholders.
- Producing regular status reports for senior leadership, clearly communicating scope, progress, risks, and decisions.
- Proactively surfacing and resolving blockers, issues, and risks before they become critical.
Key Working Relationships:
- Maintains a productive working relationship with other project managers, business owners, AI project leads, senior sponsors of AI strategy initiatives, legal, security, and data protection teams, system users, and vendors.
Position Reports to: AI Governance and Transformation Lead
Position Reports in MIP to: Director, IT Project and Portfolio Management
Position directly supervises: N/A
Indirect Reporting: N/A
Other Internal and/or external contacts:
*Internal:*
- Headquarters \& Global Offices Teams – multiple departments
- Project Business Owners, business project team members outside IT, and wider stakeholders
- Project Sponsor and Steering Committee members
- Cross\-functional AI management teams
- AI Community of Practice (CoP) leads and members
*External:*
- Vendors and Consultants
Job Requirements:
Experience / Education
- 6\+ years of project management experience in IT or technology\-driven environments.
- Demonstrated success leading complex, multi\-stakeholder programs with significant technology components.
- Bachelor's degree required.
- Experience with AI projects — whether in a project management, product, or operational capacity — strongly preferred.
- Experience in international NGO or global humanitarian organizations preferred.
- PMP, CSM, or equivalent project/program management certification preferred.
Skills / Competencies:
- Agile \& Program Management Demonstrated, hands\-on experience with Agile methodologies — including Scrum, sprint planning, backlog management, and retrospectives — is required. Proficiency with project management tools such as Jira, Monday.com, or equivalents.
- AI Literacy \& Responsible AI Familiarity with AI concepts, use cases, and the compliance, security, data privacy, and ethical considerations that responsible AI adoption requires.
- Communication \& Executive Influence Exceptional written and verbal communication skills, with the ability to tailor messaging from technical working teams through to senior executive leadership. Demonstrated ability to influence without authority — including managing up, keeping senior stakeholders aligned and accountable, and driving decisions in complex organizational environments.
- Proactivity \& Adaptability A self\-starter who moves fast, takes initiative, and creates structure in ambiguous environments. Comfortable operating in a space that is still evolving — where processes are being built, priorities shift, and the ability to adapt quickly is essential.
- Stakeholder Partnership Ability to build trusted, productive relationships across technical and non\-technical teams, across functions, and across geographies. Skilled at working in matrixed environments without direct authority over contributors.
- Problem Solving \& Risk Management Strong analytical and problem\-solving skills. Proactively identifies risks and blockers and develops mitigation strategies before issues escalate.
Working Environment:
- The position can be fully remote, with an in\-person office setting available for staff located near IRC’s New York City Headquarters location or in London if the candidate is from the UK.
- Standard working hours.
- Minimal travel may be required.
Compensation: (US *Pay Range: $88,277\-$103,222/yr); (UK Pay Range: £49,598\.90\-£60,040\.78/yr)* Posted pay ranges apply to US\-based candidates. Ranges are based on various factors including the labor market, job type, internal equity, and budget. Exact offers are calibrated by work location, individual candidate experience and skills relative to the defined job requirements.
PROFESSIONAL STANDARDS
All International Rescue Committee workers must adhere to the core values and principles outlined in IRC Way \- Standards for Professional Conduct. Our Standards are Integrity, Service, Equality and Accountability. In accordance with these values, the IRC operates and enforces policies on Safeguarding, Conflicts of Interest, Fiscal Integrity, and Reporting Wrongdoing and Protection from Retaliation. IRC is committed to take all necessary preventive measures and create an environment where people feel safe, and to take all necessary actions and corrective measures when harm occurs. IRC builds teams of professionals who promote critical reflection, power sharing, debate, and objectivity to deliver the best possible services to our clients.
Cookies: https://careers.rescue.org/us/en/cookiesettings
Compensation: Posted pay ranges apply to US\-based candidates. Ranges are based on various factors including the labor market, job type, internal equity, and budget. Exact offers are calibrated by work location, individual candidate experience and skills relative to the defined job requirements.
US Benefits: We offer a comprehensive and highly competitive set of benefits. In the US, these include: 10 sick days, 10 US holidays, 20\-25 paid time off days depending on role and tenure, medical insurance starting at $163 per month, dental starting at $6\.50 per month, and vision starting at $5 per month, FSA for healthcare and commuter costs, a 403b retirement savings plans with immediately vested matching, disability \& life insurance, and an Employee Assistance Program which is available to our staff and their families to support counseling and care in times of crisis and mental health struggles.
Equal Opportunity Employer: IRC is an Equal Opportunity Employer. IRC considers all applicants on the basis of merit without regard to race, sex, color, national origin, religion, sexual orientation, age, marital status, veteran status, disability or any other characteristic protected by applicable law.
\#li\-1
Salary Context
This $49K-$60K range is in the lower quartile 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 International Rescue Committee, 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 ($54K) sits 70% below the category median. Disclosed range: $49K to $60K.
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.
International Rescue Committee AI Hiring
International Rescue Committee has 4 open AI roles right now. They're hiring across AI/ML Engineer. Based in New York, NY, US. Compensation range: $60K - $100K.
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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