The Payments AI/ML Foundation team builds the shared platforms, services, and guardrails that enable product and data teams across Airbnb Payments to deliver trustworthy, efficient, and scalable AI capabilities.

As a Senior Software Engineer on Payments AI/ML Foundation, you will:

• Design and own core platform components that power AI across Airbnb Payments
• Partner with product, infra, data science, and operations to translate ambiguous requirements into robust systems with clear SLAs
• Build tooling and automation that makes AI development safer and faster
• Raise the bar on reliability, performance, and governance for models and agents in production

A typical day for this role will involve envisioning, championing, and supporting the development of novel ML systems, product integrations, and performance optimizations to solve real-world problems.

You will work collaboratively with cross-functional partners including software engineers, product managers, operations and data scientists, identify opportunities for business impact, understand, refine, and prioritize requirements for AI/ML models, drive engineering decisions, and quantify impact.

Hands-on productionize and operate AI/ML solution and pipelines at scale, including both batch and real-time use cases.

Lead, mentor, challenge and grow enthusiastic, collaborative AI/ML culture within the organization.

Your expertise should include:

• A degree in Computer Science or equivalent qualification
• 7+ years of industry experience in backend/platform engineering (or equivalent), including ownership of production systems
• Strong programming skills in Python, plus solid data engineering foundations
• Good to have experience with AI frameworks (Langraph, Strand etc), orchestration (Airflow/Kubeflow), and streaming/processing (Kafka/Spark/Ray)
• Proven track record building observability for AI systems (metrics/logging/traces), with automated alerting, dashboards, and SLO management
• Experience designing model governance and safety guardrails (prompt/version control, red-teaming, policy checks, approvals)
• Demonstrated ability to drive performance/cost optimizations (profiling, batching, caching, quantization, autoscaling) in high-traffic environments
• Practical familiarity with vector search/embedding pipelines (indexing strategies, consistency, reindexing, retention)

Our commitment to inclusion and belonging:

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions.

All qualified individuals are encouraged to apply.

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This role sits at the intersection of AI/ML, autonomy, model lifecycle, infrastructure, and product strategy. The PM partners closely with engineering, AI research, Hivemind Solutions, and field teams to deliver the tooling that enables sovereign autonomy, AI Factories at the edge, and continuous learning,capabilities that are central to Shield AI's strategic direction.

This is a high-impact role for an experienced product leader excited to define how foundation models are trained, validated, governed, and deployed across thousands of autonomous systems in highly contested environments.

Responsibilities:

• AI Model Development & Training Platform

Own the roadmap for foundation model training workflows, including dataset ingestion, curation, labeling, synthetic data generation, domain model training, and distillation pipelines. Define requirements for world models, robotics models, and VLA-based training, evaluation, and specialization. Lead the evolution of MLOps capabilities in Forge, including data lineage, experiment tracking, model versioning, and scalable evaluation suites.

• Data, Simulation & Synthetic Data Factory

Define product requirements for synthetic data generation, simulation-integrated data flywheels, and automated scenario generation. Partner with Digital Twin, Simulation, and autonomy teams to convert natural-language mission inputs into data needs, training procedures, and model variants.

• Safe Deployment & Model Governance

Lead the development of model governance and auditability tooling, including model cards, dataset rights, lineage tracking, safety gates, and compliance evidence. Build guardrails and workflows to safely deploy models onto edge hardware in disconnected, GPS- or comms-denied environments. Partner with Safety, Certification, Cyber, and Engineering teams to ensure traceability and evaluation pipelines meet operational and accreditation requirements.

• Edge Deployment & AI Factory Integration

Partner with Pilot, EdgeOS, and hardware teams to integrate foundation-model-based perception and reasoning into autonomy behaviors. Define requirements for distillation, quantization, and inference tooling as part of the “three-computer” development and deployment model. Ensure closed-loop workflows between cloud model training and edge-native execution.

• Cross-Functional Leadership

Collaborate with Engineering, Research, Product, Customer Engagement, and Solutions teams to ensure model outputs meet mission and platform constraints. Translate advanced AI capabilities into intuitive workflows that platform OEMs and partner nations can use to build sovereign AI factories. Sequence foundational capabilities that unblock autonomy, simulation, and customer-facing product teams.

• User & Customer Impact

Develop deep empathy for ML engineers, autonomy developers, and Solutions engineers who rely on the platform. Capture operational data gaps, mission-driven model needs, and domain-specific specialization requirements. Lead demos and onboarding for model-development capabilities across internal and external teams.

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About this role

We are seeking a highly skilled Quantitative Modeler to join our Model Governance team in Budapest. As a Quantitative Modeler, you will be responsible for developing and implementing methodologies, thresholds, and boundary conditions for Fixed Income Derivative Models.

What You Will Be Doing

• Develop and implement methodologies, thresholds, and boundary conditions for Fixed Income Derivative Models.
• Analyze model output and time-series data to define correctness criteria and thresholding to be measured every day.
• Implement such tests in Python and interact with Model Risk Management to get Model Performance Monitoring Tests approved.
• Develop and maintain Model Infrastructure, including Reporting Infrastructure for Model Breaches and Infrastructure for monitoring overnight performance tests.
• Create and maintain Model Documentation.
• Collaborate with the AI team to develop and implement a Large Language Model (LLM) project for Model Governance.

What We're Looking For

• A master's degree in a Quantitative field.
• 5+ years of experience in a quant/quant-dev finance role with strong programming skills.
• Advanced hands-on Python programming skills.
• Basic C++ coding skills.
• Expertise with Software Engineering Tools/Platforms – Git/LINUX.
• A passion for programming and a willingness to learn and adapt to new technologies.
• An analytical frame of mind and the ability to analyze complex data and make informed decisions.
• Excellent communication skills and the ability to explain complex concepts to non-technical people.

Our benefits

• Retirement investment and tools designed to help you build a sound financial future.
• Access to education reimbursement.
• Comprehensive resources to support your physical health and emotional well-being.
• Family support programs.
• Flexible Time Off (FTO) so you can relax, recharge, and be there for the people you care about.

Our hybrid work model

BlackRock's hybrid work model is designed to enable a culture of collaboration and apprenticeship that enriches the experience of our employees, while supporting flexibility for all. Employees are currently required to work at least 4 days in the office per week, with the flexibility to work from home 1 day a week. Some business groups may require more time in the office due to their roles and responsibilities.

About BlackRock

At BlackRock, we are all connected by one mission: to help more and more people experience financial well-being. Our clients, and the people they serve, are saving for retirement, paying for their children's educations, buying homes, and starting businesses. Their investments also help to strengthen the global economy: support businesses small and large; finance infrastructure projects that connect and power cities; and facilitate innovations that drive progress.

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