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XPRIZE Overview
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XPRIZE is an established global leader in designing and executing large\-scale competitions to solve humanity’s greatest challenges. As a 501(c)3, our unique model democratizes innovation by incentivizing crowd\-sourced, scientifically viable solutions to create a more equitable and abundant future for all. Since our founding in 1994, we’ve launched $519 million in prize competitions that are driving more than $31 billion in social and economic impact — a 60x return on philanthropic investment. These competitions not only de\-risk early\-stage breakthrough ideas but also mobilize capital, talent, and momentum to accelerate solutions from concept to real\-world scale.
We operate across 5 areas of impact, including:
- Deep Technology \+ Exploration
- Energy \+ Climate \+ Nature
- Food \+ Water \+ Waste
- Health
- Learning \+ Society
Join XPRIZE to help create meaningful impact as we strive to empower humanity to achieve breakthroughs and architect a more equitable and abundant future for all.
Position Description
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The XPRIZE Foundation is seeking a leader for the Energy Efficient AI Prize, an ambitious upcoming global competition designed to accelerate breakthroughs in dramatically reducing the energy intensity and carbon footprint of artificial intelligence infrastructure and computation.
As AI scales to solve humanity’s greatest challenges, its underlying infrastructure is driving an unsustainable exponential curve in global power demand. Data center energy needs could consume a significant portion of globally generated electricity within the coming decades if current trends continue. The goal of this prize is to decouple the advancement of AI from massive carbon footprints and grid\-destabilizing power consumption.
The Energy Efficient AI XPRIZE is a 12\-15 month global competition designed to demonstrate a 10x reduction in the energy consumption required for AI inference (i.e., “Less watts per correct thought”). Another way to look at this goal is 10x greater “cognitive efficiency” per unit power. The Prize is method agnostic; it aims to catalyze innovations across AI model efficiency, compute optimization, cooling systems, hardware acceleration, data center architecture, software optimization, energy\-aware training and inference, and other transformative approaches. Claims of 10X or greater energy\-efficiency will be measured against a baseline that represents today’s state\-of\-the\-art methods, with a 500M\-1B parameter open\-source model and commercial\-off\-the\-shelf hardware.
The Technical Prize Director, reporting to the Domain Lead, is a deep subject matter expert in AI infrastructure, model deployment and testing, and is responsible for the overall operations and management of the Prize competition, including coordination of operations, team relations, marketing, contract negotiations, partnerships, technical validation, and budget oversight.
This individual will be responsible for all aspects of prize operations, ensuring that the competition's rigorous scientific metrics are flawlessly executed. They will serve as the primary architect of the competition's operational lifecycle, managing a complex ecosystem of tech giants, benchmarking consortiums, data science platforms, and global competitors. They must also be able to clearly communicate highly technical concepts to non\-technical stakeholders, executives, sponsors, media, and the public, while serving as a respected and credible representative of the Prize within the global AI, energy and technology communities.
Responsibilities
- Provide leadership and managerial direction to the Prize team.
- Execute the Prize vision, strategies, milestones, testing, and stated objectives.
- Proactively manage and ensure timely response to changing needs, requirements, issues, and direction while keeping all constituents informed.
- Oversee budget and authorization of expenditures within budgetary limits; develop and implement cost control measures and operational processes.
- Lead development of technical measurement, validation, and verification criteria to assess energy efficiency, computational performance, scalability, and real\-world impact.
- Refine overall judging criteria and manage the Prize judging process, assisting judging panel members and technical advisors as needed, and maintaining impartial standards.
- Execute all technical aspects of the competition, ensuring the integrity of the "at\-the\-wall" power measurement protocol and unbiased measurements of competitor systems.
- Lead development of public/private leaderboards capable of transparently demonstrating competitor progress.
- Oversee the verification funnel, ensuring teams transition smoothly from "at\-home" remote evaluations on public/private leaderboards to mandatory, in\-person on\-site audits conducted by external partners in a controlled setting.
- Partner with XPRIZE internal stakeholders to secure, retain, and effectively manage personnel, materials, and resources needed to execute the competition successfully.
- Identify and engage industry experts, researchers, consultants, and advisors to support the Prize on a temporary and/or contract basis.
- Monitor and report on Prize progress to XPRIZE leadership, advisory boards, sponsors, partners, and external stakeholders, ensuring all requirements are met.
- Organize, host, and participate in conferences, workshops, and events globally to promote the competition, recruit teams, and support judging and award activities.
- Ensure the competition is conducted in line with XPRIZE Foundation rules, policies, and operational processes, as well as specific Prize guidelines.
- Serve as a public\-facing ambassador for the Prize through speaking engagements, media interviews, conferences, thought leadership, blogs, webinars, and industry outreach.
- Collaborate cross\-functionally across departments and facilitate effective communication and alignment among internal and external stakeholders.
- Develop high\-quality project plans that support reliable execution and operational excellence.
Qualifications
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- Subject Matter Expert with demonstrated expertise across one or more of the following areas:
+ Energy\-efficient AI systems
+ AI infrastructure and data center optimization
+ High\-performance computing
+ Sustainable computing architectures
+ AI model optimization and inference efficiency
+ Cloud computing infrastructure
+ Grid\-aware or carbon\-aware computing systems
+ Data center energy systems and cooling technologies
+ Renewable energy integration for computing infrastructure
- Advanced degree required (PhD preferred) in computer science, electrical engineering, AI/ML, energy systems, data science, physics, or another technical field highly relevant to the goals of this Prize.
- At least 7 years of experience in academic, research, startup, hyperscaler, or industry environments related to AI infrastructure, computing systems, hardware engineering or data center architecture. Familiarity with MLPerf, power measurement protocols, and large language model inference pipelines is highly desired.
- Demonstrated experience leading complex, multidisciplinary technology initiatives.
- Strong analytical, strategic thinking, and problem\-solving skills.
- Ability to thrive in fast\-moving, ambiguous, and entrepreneurial environments with evolving priorities and timelines.
- Ability to deeply understand, refine and clearly explain complex technical protocols, including gRPC APIs, just\-in\-time (JIT) data delivery systems, and cryptographic dataset handling.
- Excellent public speaking and communication skills, including the ability to translate complex technical concepts to broad and diverse audiences.
- Strong relationship\-building skills with researchers, industry leaders, startups, sponsors, and global partners.
- Passion for leveraging technology and innovation to solve global sustainability challenges.
- Belief that a small group of motivated individuals can truly change the world for the better.
Why Work at XPRIZE:
In addition to working for a mission\-driven company that catalyzes industries, pushes innovation forward, and is creating an abundant and equitable future, we offer the following benefits:
- Remote\-first environment (must live and work in the United States)
- Quarterly company\-paid All\-Hands meetings in Los Angeles for frequent in\-person collaboration
- Employee and dependent medical, dental, and vision options
- A 401(K) program with employer match
- Ample paid time off, including vacation, floating holidays, sick days, and company\-paid holidays
- An Employee Assistance Program for confidential, professional support with personal, family, or other challenges
- Employee stipends/reimbursements for cell phone, internet, health \& wellbeing, and learning \& development
- Generous Paid Parental Leave for all employees welcoming a new child to their family
- One meeting\-free block per week and four focus weeks per year to ensure uninterrupted time for strategic projects
The anticipated base salary for this position is $170,000 to $200,000 and may also qualify for an annual incentive. This role is eligible for our extensive benefits package and generous paid time off including vacation, sick, and holidays. The actual base salary offered will depend on a variety of factors including the qualifications of the individual applicant, years of relevant experience for the role, level of education attained, and certifications and/or other licenses held. XPRIZE is a remote\-first environment.
The XPRIZE FOUNDATION is an equal opportunity employer and does not unlawfully discriminate in employment. Equal access to employment, services, and programs is available to all persons. Those applicants requiring reasonable accommodation to the application and/or interview process should notify a representative of the organization.
Please note: Though submitting a resume to the XPRIZE FOUNDATION implies that you are interested in a position(s), it does not imply that you are an applicant. You are not considered an applicant until you have been contacted directly by a Talent Acquisitions representative requesting that you begin the designated application process, which may involve phone and/or in\-person interview(s), job\-related testing, and background checks.
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Salary Context
This $170K-$200K range is above 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 XPRIZE 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. Director-level AI roles across all categories have a median of $247,800. Disclosed range: $170K to $200K.
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.
XPRIZE Foundation AI Hiring
XPRIZE Foundation 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 $170,000 across 1,926 positions. About 15% 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 3,823 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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