Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million

hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique

stays and experiences that make it possible for guests to connect with communities in a more authentic way.

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million

hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique

stays and experiences that make it possible for guests to connect with communities in a more authentic way.

The Community You Will Join:

Machine Learning and Artificial Intelligence are at the heart of the Airbnb product. From Trust to Payments, and from Customer

Service to Marketing we rely on ML to ensure that guests and hosts have the best possible experience with Airbnb.

The CS AI product team is responsible for driving CSxAI (Customer Support x Artificial Intelligence) initiatives by adopting the

Generative AI technologies to enable an intelligent, scalable and exceptional service experience. The team develops and enhances

various AI models, ML services and tools including LLM fine-tuning, alignment and optimization, RAG/Search, LLM evaluation and

testing automation, feedback-based learning and guardrail for a wide range of applications in Airbnb.

What you will do:

As a principal machine learning engineer, you will be responsible for fine-tuning state-of-the-art LLMs for diverse use cases

while optimizing models for high-performance deployment on Airbnb’s ML Infrastructure. You will partner with product managers,

software engineers, data scientists and operation teams to brainstorm, design and develop AI products such as AI Assistant,

Autonomous agent, recommendation, travel planning, and many more products that make meaningful impacts in the world of travel.

Your responsibilities:

Work with large scale structured and unstructured data; explore, experiment, build and continuously improve foundation models

for Airbnb product, business and operational use cases.

Create a multi-year tech roadmap that enables our team to stay on the leading edge of the rapidly evolving AI landscape and

leverage the best in class technologies to deliver customer benefits.

Continuously evaluate recent and upcoming large foundational models, ensuring the selection and refinement of the highest

quality models for enhanced performance and efficiency.

Hands-on prototype, develop and productionize LLM models and pipelines at scale, including both batch and real-time use cases.
Drive key AI architectural decisions for products, and contribute to Airbnb’s ML platform architecture and strategy.

MINIMUM QUALIFICATIONS:

PhD in Computer Science, Machine Learning, Mathematics, Statistics, or related technical field.
10+ years of experience with developing machine learning models and products at scale from inception to business impact.
Programming experience in Python and hands-on experience with frameworks such as PyTorch.
Proven record of training, fine tuning, optimizing models and inference run-time
Post-training experience in areas like data processing for fine-tuning; responsible LLMs; LLM alignment; reinforcement

learning; efficient training and inference; language model evaluation; and/or multilingual and multimodal modeling.

Or specialized experience in runtime optimizations, model quantization, compression, on-device inference, GPU inference,

pytorch, kernel development

PREFERRED QUALIFICATIONS:

PhD in AI, machine learning, data science, or related technical fields.

Publications at peer-reviewed AI conferences (e.g., NeurIPS, CVPR, ICML, ICLR, ICCV, and ACL).

Customer Support Systems: Experience with AI technologies in customer support applications.
Agile Practice for AI production: Experience with the entire AI product development lifecycle from incubation to production at

scale, following agile practices in the Applied AI/ML domain.

Infrastructure Acumen: Experience deploying and scaling business-critical AI services and driving architectural requirements on

ML infrastructures

Your Location:

This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as

agreed to with your manager. While the position is Remote Eligible, you must live in a state where Airbnb, Inc. has a registered

entity. Click here for the up-to-date list of excluded states. This list is continuously evolving, so please check back with us if

the state you live in is on the exclusion list . If your position is employed by another Airbnb entity, your recruiter will inform

you what states you are eligible to work from.

Our Commitment To Inclusion & 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.

We strive to also provide a disability inclusive application and interview process. If you are a candidate with a disability and

require reasonable accommodation in order to submit an application, please contact us at: reasonableaccommodations@airbnb.com.

Please include your full name, the role you’re applying for and the accommodation necessary to assist you with the recruiting

process.

We ask that you only reach out to us if you are a candidate whose disability prevents you from being able to complete our online

application.

How We'll Take Care of You:

Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training,

transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be

modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.

Pay Range

$292,000—$365,000 USD

Role

Principal Machine Learning Engineer- LLM Fine-tuning and Optimization

Similar Jobs

Principal AI/ML Researcher / Engineer In Reasoning, Planning, and Decision-making systems

Airbnb

United States•Posted: Jun 3•Deadline: Aug 17

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. ABOUT THE ROLE We are seeking a Principal / Distinguished AI/ML Researcher and/or Engineer with deep experience in reasoning, planning, and decision-making systems. This role is ideal for individuals who have architected post-training intelligence frameworks, integrated Large Reasoning Models (LRMs) with Knowledge Graphs, and applied Reinforcement Learning (RL) as a first-class component of adaptive planning and control. You will be responsible for inventing, scaling, and operationalizing intelligent decisioning substrates that blend symbolic and sub-symbolic methods, enabling next-generation AI systems that go beyond pattern recognition into the realm of deliberation, foresight, and agency. Our mission is to build cognitive AI systems that combine post-trained foundational models, explicit memory and knowledge, and recursive planning strategies to power sophisticated real-world decisioning in personalized environments. You will collaborate across disciplines and influence company-wide AI architecture. A core dimension of this role is the design and deployment of multi-agent systems, where reasoning, planning, and decisioning are distributed across networks of intelligent agents. You will formulate coherent, synergistic strategies that enable agents to cooperate, negotiate, and align objectives, ensuring that distributed intelligence converges to purposeful, high-quality outcomes across contexts. RELEVANCE AND IMPACT OF THIS ROLE This role advances Airbnb's AI capabilities toward reasoning, planning, and adaptive decision-making across complex real-world environments. The near-term impact spans improved decision quality, contextual intelligence, adaptive personalization, and operational coordination across guest and host workflows — introducing goal-directed reasoning systems capable of handling ambiguity, constraints, trade-offs, and multi-step planning. Guests benefit from more intelligent planning and assistance, while hosts and internal teams gain systems capable of adaptive optimization, dynamic recommendations, policy-aware decisioning, and intelligent workflow orchestration. Longer term, this role helps establish Airbnb's leadership in cognitive AI systems and distributed intelligence architectures. The technologies developed here become the decisioning and reasoning substrate underlying the broader ecosystem — enabling AI systems that can deliberate, coordinate, adapt, and make coherent long-horizon decisions across multiple agents and environments. Over time, this positions Airbnb as an intelligent coordination and planning platform where AI systems actively reason, plan, and coordinate actions across the marketplace in ways that continuously improve user outcomes, ecosystem health, and strategic adaptability. WHAT YOU WILL DO RESEARCH & INNOVATION * Drive foundational and applied research in reasoning engines, planning architectures, and decision-making frameworks at scale in order to incorporate genAI into the ranking / recommendation / personalization stack in both single model to multi-agent ( system ) level intelligence with objective to grow the business (new user growth, abandoned user, long tailed user) in existing and new business areas while supporting Multi-Modal NL → Conversational Interfaces. * Advance techniques in LLM/LRM post-training, reinforcement learning–based decisioning, and knowledge-integrated agents. * Design methods for plan induction, value estimation, and contingency modeling within intelligent agents. * Explore and validate protocols for distributed reasoning and joint planning among cooperative agents in multi-agent systems. SYSTEM DESIGN & ARCHITECTURE * Architect RPD systems that integrate post-trained LLMs/LRMs, graph-structured memory (e.g., KGs), and RL-driven controllers. * Design recursive task planners, search-based or policy-based reasoners, and belief-state trackers that can interoperate with large model substrates. * Ensure modularity and extensibility through multi-agent frameworks, agentic substrates, and declarative planning pipelines. * Define communication protocols, coordination strategies, and cross-agent knowledge alignment mechanisms to foster emergent cooperative intelligence. MODEL DEVELOPMENT * Build and evolve stateful, dynamic models that combine supervised learning with online/offline reinforcement, simulation-based rollouts, and symbol grounding. * Implement hybrid pipelines that couple learned embeddings, prompted generative models, and graph-theoretic inference. * Optimize systems for adaptive exploration, planning horizon control, and policy robustness. * Develop frameworks for distributed value propagation, multi-agent credit assignment, and global planning from local agents. TECHNICAL LEADERSHIP * Set direction for planning/reasoning infrastructure within the AI/ML platform strategy. * Serve as the technical conscience and architectural leader across high-stakes AI initiatives involving autonomous agents or high-fidelity decision pipelines. * Mentor teams in systems thinking, causal modeling, symbolic-connectionist integrations, and long-term planning under uncertainty. * Lead development of multi-agent reasoning systems, defining principles for inter-agent knowledge exchange, goal delegation, and cooperative decision resolution. COLLABORATION * Work across disciplines—product, infra, and design—to translate ambiguous product intent into multi-stage reasoning pipelines. * Partner with researchers, ontologists, and ML engineers to encode world knowledge, goals, and values into usable inference artifacts. * Contribute to a company-wide understanding of what it means to make intelligent choices, not just predictions. * Collaborate with internal teams on distributed agent coordination, shared memory protocols, and policy harmonization across decision surfaces. OPERATIONAL EXCELLENCE * Productionize real-time reasoning loops with low-latency inference, caching, retrieval-augmented generation, and streaming updates to symbolic memory. * Deploy post-training hooks for inserting logic, constraints, and domain priors into existing large models. * Create advanced monitoring, attribution, and evaluation pipelines for agent behavior and decision quality. * Operationalize multi-agent orchestration, ensuring reliable and fault-tolerant communication and decision propagation. MINIMUM QUALIFICATIONS * Masters or equivalent in Computer Science, AI, Cognitive Science, or related fields. * Recent published work or patents in AI, Cognitive Science, or related fields. * 15+ years in AI/ML, including post-training architectures and production-scale reasoning systems. * Advanced coding proficiency in Java, Python, C++, or similar, with experience in ML/RL frameworks (e.g., PyTorch, Ray, JAX, RLlib) at scale. * Proven experience integrating LLMs/LRMs with Knowledge Graphs or structured world models. * Deep understanding of Reinforcement Learning and its application to decisioning and planning. * Fluency in hybrid model architectures: connectionist-symbolic fusion, retrieval-based agents, or goal-directed transformers. * Experience working on multi-agent coordination, distributed RL, or cooperative inference systems. PREFERRED QUALIFICATIONS * Ph.D. in AI, Machine Learning, Robotics, Cognitive Systems, or related areas. * Published work or patents in multi-agent reasoning, plan synthesis, knowledge-augmented learning, or generative control. * Experience in cognitive architectures, neuro-symbolic systems, or agent-based simulation environments. * Demonstrated ability to lead cross-functional research-to-production transitions. * Experience with memory architectures, task graphs, or semantic program induction. * Prior work on distributed intelligence platforms with explicit agent interaction models and collective decision-making logic. Your Location: This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed to with your manager. While the position is Remote Eligible, you must live in a state where Airbnb, Inc. has a registered entity. Click here for the up-to-date list of excluded states. This list is continuously evolving, so please check back with us if the state you live in is on the exclusion list . If your position is employed by another Airbnb entity, your recruiter will inform you what states you are eligible to work from. Our Commitment To Inclusion & 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. We strive to also provide a disability inclusive application and interview process. If you are a candidate with a disability and require reasonable accommodation in order to submit an application, please contact us at: reasonableaccommodations@airbnb.com. Please include your full name, the role you’re applying for and the accommodation necessary to assist you with the recruiting process. We ask that you only reach out to us if you are a candidate whose disability prevents you from being able to complete our online application. How We'll Take Care of You: Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits. Pay Range $296,000—$370,000 USD

Principal AI/ML Researcher / Engineer In Bayesian, Large Foundational Systems, and Distributional Reinforcement Learning

Airbnb

United States•Posted: Jun 3•Deadline: Aug 17

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way. ABOUT THE ROLE We are seeking a seasoned Principal AI/ML Researcher and Engineer with deep expertise in Bayesian Learning, and Distributional Reinforcement Learning (RL) to lead the advanced research and development of cutting-edge intelligence AI models. These systems will integrate foundational Bayesian frameworks with advanced architectures, including Mixture of Models, multi-pass sharded systems, multitask and multi-objective optimization, and external knowledge incorporation. Additionally, the role involves innovating ways to interoperate and integrate Large Language Models (LLMs) and Large Multimodal Models (LMMs) with Reasoning, Planning, and Decisioning abilities into the Bayesian frameworks to create a seamless foundational model fabric that synergizes with diverse model ecosystems.The role will require ensuring these models and supporting systems perform efficiently at scale, integrating them into live systems that directly impact product and user experience. Our goal is to build next-generation AI platforms that redefine personalization, decision-making, and intelligence across diverse applications. You will work on developing production-level systems, collaborate with cross-functional teams, and play a pivotal role in shaping our AI/ML strategy. RELEVANCE AND IMPACT OF THIS ROLE This role drives Airbnb's evolution toward probabilistic, uncertainty-aware intelligence systems capable of reasoning under ambiguity and learning continuously from dynamic environments. The near-term impact spans improved personalization quality, ranking quality, uncertainty estimation, and adaptive decision-making across guest and host experiences — enabling policy-driven intelligence that handles long-tail discovery, evolving preferences, and complex marketplace dynamics. Longer term, this role helps establish Airbnb's leadership in adaptive probabilistic intelligence by building the foundational substrate that connects Bayesian learning, reinforcement learning, foundational models, multi-agent orchestration, and large-scale personalization into a unified adaptive architecture — where AI systems continuously balance exploration, exploitation, uncertainty, and ecosystem optimization at scale. WHAT YOU WILL DO RESEARCH & INNOVATION: * Lead groundbreaking applied research in Bayesian systems, distributional reinforcement learning, and multi-modal architectures to drive novel advances in AI and Foundational Intelligence (Ranking, Recommendations, Personalization) to fill out gaps in the Long Tail Curve of Discovery in order to grow the Business Offerings on both Guest and Host Long Tail Ends * Bridge the gap between theoretical AI/ML advancements and real-world production systems * Ensure that new research can be effectively applied and scaled to meet practical needs. ARCHITECT AND DESIGN: * Define and drive the architecture of large-scale Bayesian Framework-based AI systems at Airbnb. * Develop multi-pass sharded Bayesian + Discriminative/Generative single to multi agent systems for scale and efficiency. * Incorporate Mixture of Models and Agents, multitask learning, multi-objective optimization, and external knowledge systems into model designs. * Innovate methods to interoperate with LLMs, LRMs, LMMs, and transformer-based architectures, ensuring seamless integration and collaboration within the AI ecosystem using AI Multi-Agentic Frameworks. MODEL DEVELOPMENT: * Build and refine Bayesian or Markovian Graph chains to incorporate uncertainty estimation, adaptive decision-making, and probabilistic reasoning. * Develop foundational models by merging Bayesian techniques with Classical ML with L[L/M/R]Ms and other advanced architectures, ensuring compatibility and synergy. * Continuously improve systems for scalability, performance, and robustness, enabling models to absorb and adapt to diverse data sources and paradigms. TECHNICAL LEADERSHIP: * Lead technical direction and strategy for AI/ML systems. * Influence cross-functional teams, including engineering leaders, product managers, and data scientists, to adopt unified intelligence platform approaches. * Perform code reviews, mentor engineers, and champion best practices in AI/ML. COLLABORATION: * Work with structured and unstructured data to design models for diverse use cases. * Collaborate with cross-functional partners to identify opportunities, refine requirements, and drive impactful solutions. * Translate complex technical decisions into business value. OPERATIONAL EXCELLENCE: * Develop, productionize, and maintain scalable AI/ML pipelines, including batch and real-time use cases. * Implement advanced model evaluation systems, including interpretability, hyperparameter optimization, and drift detection. * Ensure system reliability and performance through rigorous testing and validation. MINIMUM QUALIFICATIONS * Master's degree in Computer Science, Mathematics, or a related technical field (or equivalent practical experience). * 15+ years of technical experience in Applied Machine Learning, including producing code and deploying production systems. * Strong programming skills in Python, Scala, Java, or C++, with expertise in AI/ML frameworks (e.g., TensorFlow, PyTorch). * Proven experience with Bayesian Neural Networks, Bayesian Learning, and Reinforcement Learning. * Strong math background in probability, statistics, and optimization. * Experience with building scalable AI/ML systems using technologies like Spark, Kafka, and distributed architectures. * Familiarity with advanced ML techniques, including Mixture of Models, Ensemble Techniques, multitask learning, and sharded architectures. PREFERRED QUALIFICATIONS * Ph.D. in a relevant technical field with 15+ years of experience in AI/ML research and engineering. * Expertise in architecting and leading large-scale AI/ML systems with enterprise-level impact. * Hands-on experience with multitask and multi-objective optimization systems. * Experience in designing knowledge-driven systems and integrating external knowledge sources. * Familiarity with foundational models, transformers, and their role in interoperating with Bayesian systems. * Exceptional leadership, collaboration, and communication skills in complex, matrixed organizations. * Strong track record of publishing research or developing novel AI/ML techniques. Your Location: This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed to with your manager. While the position is Remote Eligible, you must live in a state where Airbnb, Inc. has a registered entity. Click here for the up-to-date list of excluded states. This list is continuously evolving, so please check back with us if the state you live in is on the exclusion list . If your position is employed by another Airbnb entity, your recruiter will inform you what states you are eligible to work from. Our Commitment To Inclusion & 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. We strive to also provide a disability inclusive application and interview process. If you are a candidate with a disability and require reasonable accommodation in order to submit an application, please contact us at: reasonableaccommodations@airbnb.com. Please include your full name, the role you’re applying for and the accommodation necessary to assist you with the recruiting process. We ask that you only reach out to us if you are a candidate whose disability prevents you from being able to complete our online application. How We'll Take Care of You: Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits. Pay Range $296,000—$370,000 USD

Principal, Data Analytics (Adobe - AA/CJA/WebSDK)

DEPT

United States•Posted: Jul 1•Deadline: Aug 16

WHY DEPT®? We are pioneers at heart. What this means, is that we are always leaning forward, thinking of what we can create tomorrow that does not exist today. We were born digital and we are a new model of agency, with a deep skillset in tech and marketing. That’s why we hire curious, self-driven, talented people who never stop innovating. Our culture is big enough to cope and small enough to care. Meaning, that with people across 20+ countries, we’re big enough to provide you with the best tools, global opportunities, and benefits that help you thrive. While acting small by investing in you, your growth, your team, and giving you the autonomy to solve our clients problems, no matter where you are in the world. THE ROLE DEPT® is seeking a Senior Analytics & Identity Engineer to join our forward-deployed architecture squad in North America. Mapped back to our platform-agnostic Analytics Craft, this role is a hands-on technical seat focused on Analytics Craft excellence. You will specialize in web/app telemetry tracking instrumentation, tag container cleanup, and analytics validation reporting. You will step directly into complex client environments to audit and clean up double-tracked Web implementations, decommission legacy tracking tags, and configure clean client-side data collection containers. You will build real-time analytics verification procedures to identify and resolve metric differences between frontend trackers and enterprise data lakes, securing end-to-end data trust. WHAT YOU'LL DO * Optimize Telemetry & SDKs: Audit and clean up double-tracked SDK implementations, decommission legacy tracking tags, and configure clean client-side data collection containers. * Configure Event Forwarding: Configure robust server-side event forwarding mechanisms to securely route web/app behavioral telemetry into downstream customer profile platforms. * Remediate Data Discrepancies: Build real-time analytics verification procedures to identify and resolve metric differences between frontend trackers and enterprise data lakes. * Clean Up Tag Containers: Re-architect and simplify complex, bloated tag containers to improve page performance and loading latency. * Support Attribution Validation: Work hand-in-hand with web architects to optimize edge-based tagging, and journey architects to validate campaign-link attribution. WHAT YOU BRING * Telemetry & Analytics Engineering: 6+ years of software engineering experience focusing on web/app analytics instrumentation, tag management systems, or customer telemetry tracking. * Tag & Data Layer Mastery: Deep technical command of client-side data layer design, custom JavaScript tag rules, browser debugging utilities, and server-side event routing. * Required Adobe Experience: * Expert, hands-on configuration mastery across Adobe Experience Platform Web SDK and Mobile SDK (AEP WebSDK / Mobile SDK). * Direct development experience utilizing Adobe Launch (Experience Platform Data Collection), configuring extensions, rules, and server-side Event Forwarding. * Proven experience debugging data discrepancies and tracking errors using Adobe Analytics and Adobe Customer Journey Analytics (CJA). * Collaboration Skills: Ability to coordinate with frontend engineers on edge-based tag optimization and campaign attribution. Work Environment: Remote position - TRAVEL EXPECTED WHAT DO WE OFFER? * We are a collaborative, open-door, best-idea-wins environment that fosters personal and company growth and has fun doing it. Here is a snapshot of our benefits package: * Healthcare, Dental, and Vision coverage * 401k plan, plus matching * PTO * Paid Company Holidays * Parental Leave WE SUPPORT YOU BEING YOU: DEPT® is an equal opportunity employer (EOE). We believe our work is its best when our people feel safe and free to be themselves. We’re committed to an inclusive and barrier-free recruitment and selection process and workplace, regardless of anyone’s identity, background, beliefs, lifestyle or disabilities. So tell us about any accommodations you need. It’s totally confidential and only used to make sure you feel fully supported at every step. DEPT® participates in E-Verify, meaning your Form I-9 information will be sent to the federal government to confirm you are authorized to work in the U.S. We are a B Corp-certified company passionate about purpose-driven work. Our hope is that you can feel good about the contributions DEPT® is making to the world and we always have an open door for your ideas in making the world a better place. DEPT® is a pioneering technology and marketing services company that creates integrated end-to-end digital experiences for brands such as Google, KFC, Philips, Audi, Twitch, Patagonia, eBay and more. Its team of 2,500+ digital specialists across 30+ locations on 5 continents delivers pioneering work on a global scale with a boutique culture. Learn more about DEPT® Learn more about DEPT® diversity, equity, and inclusion efforts The anticipated salary range for this position is listed below. Salary is based on a range of factors that include relevant experience, expertise, physical location, and organizational impact. This is based on a 40-hour workweek and leveling. Keep in mind, we’re flexible. US Remote Range $96,200—$148,000 USD

JavaJavaScriptRust