Interested in this Research Engineer role at Adyen?
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This is Adyen
Adyen provides payments, data, and financial products in a single solution for customers like Meta, Uber, H\&M, and Microsoft \- making us the financial technology platform of choice. At Adyen, everything we do is engineered for ambition.
For our teams, we create an environment with opportunities for our people to succeed, backed by the culture and support to ensure they are enabled to truly own their careers. We are motivated individuals who tackle unique technical challenges at scale and solve them as a team. Together, we deliver innovative and ethical solutions that help businesses achieve their ambitions faster.
The Opportunity
Adyen is building a top\-tier AI engineering organization in Amsterdam, San Francisco and Madrid to drive our next chapter of innovation using AI globally across the entire company. This is a highly technical, hands\-on role focused on the exploration and application of cutting\-edge AI research within the financial technology sector. As a Senior AI Research Engineer, you will operate with a high degree of autonomy and responsibility, delivering strategic, high\-impact outcomes that bridge the gap between advanced AI research and production\-grade applications at a global scale, potentially impacting trillions of dollars in transactions annually.
What You'll Do:
- Innovate and Deploy: Drive the execution of Adyen's AI strategy, focusing on the practical application of Generative AI (GenAI) and other AI methodologies in finance. This includes contributing to Adyen's efforts in key research areas such as AI agents for data analysis and operational workflows, human\-in\-the\-loop for integrity risk, and development of foundation models. For instance, you might contribute to initiatives like the Data Agent Benchmark for Multi\-step Reasoning (DABStep), which evaluates AI agents on real\-world data analysis tasks, including those from the financial sector.
- Build Production\-grade Applications: Bridge the gap between cutting\-edge AI research and production by implementing research papers into robust, scalable, and production\-ready code. Reduce complexity and dependencies across teams by championing engineering and scientific alignment by setting high quality standards.
- Optimize and Scale: Contribute to defining the long\-term vision for AI at Adyen, specifically how AI will interact with humans and finance, including consumers, merchants, and financial institutions. This also includes understanding regulation and advocating for safe innovation in the field.
- Think Outside the Box: Drive innovation by challenging the status quo, introducing transformative ideas and implementing creative solutions to solve real\-world problems. Carry out flexible, value\-driven assignments, proactively unblocking teams to maximize organizational impact and drive strategic initiatives.
- Force Multiplier: Provide mentorship and horizontal sponsorship across the organization, fostering collaboration to share knowledge and best practices, and cultivating a culture of continuous improvement. This includes deeply engaging them in problem\-solving processes and guiding them through execution, fostering their growth through hands\-on involvement.
- Team Player: Actively pair with other engineering teams to solve deep\-rooted technical challenges and be fully capable of being hands\-on with the code, whether creating proof\-of\-concepts or fixing critical performance issues.
- Learn and Lead: Connect with the broader AI community (including startups, VCs, and AI labs) to stay informed of the latest advancements and identify potential partnership opportunities.
Who You Are:
- You are deeply embedded in the scientific AI research community and have a strong understanding of the latest SOTA advancements.
- You have significant experience and a strong understanding of Generative AI (GenAI) and Large Language Models (LLMs).
- You demonstrate a strong engineering mindset with a track record of writing clean, efficient, and scalable code suitable for production environments.
- You have demonstrated experience taking cutting\-edge AI research papers and implementing them into production\-quality code.
- You demonstrate the ability to think critically and deliver simple and elegant solutions to complex, cross\-team problems, influencing strategic direction and fostering innovation across the organization.
- You excel at translating complex technical concepts into clear, understandable terms for diverse audiences, including engineers, executives, and during public events. You adapt your communication style to effectively engage with diverse audiences.
- You thrive in leveraging empathy, influence, negotiation, relationship building, and conflict resolution to foster strong, trust\-based collaborations.
Nice to Haves:
- A strong product sense and the ability to identify impactful AI use cases.
- Experience in AI\-enabled fintech companies.
- Familiarity with classical machine learning concepts.
- Experience with external visibility activities such as conferences and publications.
- Experience working with on\-premise infrastructure.
Why Adyen?
This is an exceptional opportunity to join a solid, established company with a startup mindset, characterized by small teams, direct communication, and work on important challenges. You'll have direct access to massive global datasets (e.g., payments, identity data) and the ability to see your team's work have an immediate impact at scale. We offer an environment of ownership and speed, where a focused research team can make a significant difference. You will be at the forefront of bridging AI and fintech, shaping how these two critical areas intersect. We are looking for individuals who are eager to stay connected to the edge of AI innovation while ensuring we deliver practical value to our global platform.
Our Diversity, Equity and Inclusion commitments
Our unique approach is a product of our diverse perspectives. This diversity of backgrounds and cultures is essential in helping us maintain our momentum. Our business and technical challenges are unique, and we need as many different voices as possible to join us in solving them \- voices like yours. No matter who you are or where you're from, we welcome you to be your true self at Adyen.
Studies show that women and members of underrepresented communities apply for jobs only if they meet 100% of the qualifications. Does this sound like you? If so, Adyen encourages you to reconsider and apply. We look forward to your application!
What's next?
Ensuring a smooth and enjoyable candidate experience is critical for us. We aim to get back to you regarding your application within 5 business days. Our interview process tends to take about 4 weeks to complete, but may fluctuate depending on the role. Learn more about our hiring process here. Don't be afraid to let us know if you need more flexibility.
This role is based out of our \[CITY NAME] office. We are an office\-first company and value in\-person collaboration; we do not offer remote\-only roles.
Role Details
About This Role
Research Engineers bridge the gap between research and production. They implement papers, build experiment infrastructure, optimize training pipelines, and make research prototypes production-ready. They're the engineers who make research work at scale.
The role sits at a unique intersection. You need to understand the math well enough to implement novel architectures correctly, and you need the engineering chops to make them run efficiently on distributed systems. When a research scientist has a breakthrough idea, you're the person who turns it from a notebook prototype into a training pipeline that runs on 256 GPUs.
Across the 3,824 AI roles we're tracking, Research Engineer positions make up 2% of the market. At Adyen, this role fits into their broader AI and engineering organization.
Research Engineer roles are growing as AI labs recognize that research velocity depends on engineering quality. The role is less competitive than Research Scientist (no PhD required), but the bar for engineering skill is very high. These roles are concentrated at major labs and well-funded startups.
What the Work Looks Like
A typical week involves: implementing a new attention mechanism from a recent paper, profiling and optimizing a training pipeline that's bottlenecked on data loading, building evaluation infrastructure for a new benchmark, debugging distributed training issues across a GPU cluster, and pair-programming with a research scientist on their latest experiment. The work is deeply technical.
Research Engineer roles are growing as AI labs recognize that research velocity depends on engineering quality. The role is less competitive than Research Scientist (no PhD required), but the bar for engineering skill is very high. These roles are concentrated at major labs and well-funded startups.
Skills in Demand for This Role
Strong software engineering fundamentals plus ML knowledge. Python, C++, and CUDA experience are common requirements. You'll need to read papers and turn ideas into working code. Distributed systems experience (especially distributed training) is highly valued. Performance optimization skills separate great candidates from good ones.
Experience with large-scale training infrastructure (FSDP, DeepSpeed, Megatron), GPU programming (CUDA, Triton), and the internals of ML frameworks (PyTorch internals, custom autograd functions) is what makes candidates stand out. The best research engineers can debug issues that span the full stack from GPU memory management to numerical precision to algorithmic correctness.
Strong postings mention the team's recent research, the infrastructure scale, and the specific technical challenges. They often list the research areas you'd support. Look for roles that emphasize both implementation quality and research understanding.
Compensation Benchmarks
Research Engineer roles pay a median of $260,000 based on 401 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400.
Across all AI roles, the market median is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $97,380; Mid: $160,000; Senior: $227,400; Director: $243,000; VP: $250,000.
Adyen AI Hiring
Adyen has 1 open AI role right now. They're hiring across Research Engineer. Based in Seattle, WA, US.
Location Context
AI roles in Seattle pay a median of $228,000 across 1,009 tracked positions. That's 14% above the national median.
Career Path
Common paths into Research Engineer roles include Software Engineer, ML Engineer, Research Intern.
From here, career progression typically leads toward Senior Research Engineer, Research Scientist, ML Architect.
This is one of the best entry points into AI research without a PhD. Build a strong engineering portfolio with ML projects, contribute to open-source ML frameworks, and demonstrate that you can implement complex ideas correctly and efficiently. The transition to Research Scientist is possible with published first-author work, which some research engineer roles support.
What to Expect in Interviews
Technical screens test both engineering skill and research understanding. Expect coding rounds with performance-critical implementations (GPU optimization, efficient data loading). Be prepared to discuss papers relevant to the team's research area and explain how you'd implement key ideas. System design questions focus on training infrastructure: distributed training, experiment tracking, and compute resource management.
When evaluating opportunities: Strong postings mention the team's recent research, the infrastructure scale, and the specific technical challenges. They often list the research areas you'd support. Look for roles that emphasize both implementation quality and research understanding.
AI Hiring Overview
The AI job market has 3,824 open positions tracked in our dataset. By seniority: 119 entry-level, 1,813 mid-level, 1,472 senior, and 420 leadership roles (Director, VP, C-Level). Remote roles make up 16% of the market (613 positions). The remaining 3,187 roles require on-site or hybrid attendance.
The market median for AI roles is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($293,500 median, 31 roles); AI Safety ($274,200 median, 51 roles); Research Engineer ($260,000 median, 401 roles).
Research Engineer roles are growing as AI labs recognize that research velocity depends on engineering quality. The role is less competitive than Research Scientist (no PhD required), but the bar for engineering skill is very high. These roles are concentrated at major labs and well-funded startups.
The AI Job Market Today
The AI job market spans 3,824 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,702), Data Scientist (281), AI Software Engineer (258). 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 (119) are outnumbered by mid-level (1,813) and senior (1,472) 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 420 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 16% of all AI roles (613 positions), with 3,187 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 $200,000. Top-quartile roles start at $253,000, 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 $293,500 median, while Prompt Engineer roles sit at $142,800. 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 (1,968 postings), Aws (1,203 postings), Azure (882 postings), Rag (877 postings), Gcp (735 postings), Prompt Engineering (587 postings), Pytorch (586 postings), Claude (554 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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