דרושים Staff Data Scientist Inference ב-Airbnb ב-ארהב

The Community You Will Join:

an Android Studio plugin to supercharge IDE & Sync performance, among many others.

A Typical Day:

• Collaborate with team members & cross functional partners to identify opportunities for improving our developers’ productivity.
• Drive roadmap projects and deliver high quality results to further our mission.
• Improve our existing frameworks & build system to deliver on our ambitious vision.

Your Expertise:

• 9+ years of industry experience building Android apps using Kotlin.
• Experience building frameworks and build-systems (using Gradle, Bazel, etc.)
• Deep technical understanding of how dependency injection systems work (e.g. Dagger)
• Experience building code generation tools (e.g. annotation processors, KSP, Kotlin compiler plugins)
• Experience working in medium to large-scale codebases.
• [Nice to have] 2+ years of experience using Jetpack Compose.
• [Nice to have] Experience building Android Studio / IntelliJ IDEA plugins.
• [Nice to have] Experience using Compose for desktop.
• Ability to travel to the San Francisco office for about a week each quarter for gatherings.

Offices: United States

The difference you will make:

As a member of this team you would be working with talented engineers on building infrastructure to solve cutting edge experimentation problems. The primary focus of this position will be on our platform’s results computation stack, consisting of data pipelines, a grammar for experimentation, and an analysis engine. You will bring a deep understanding of data processing, API design and experimentation methodology to help us reliably and accurately calculate results at scale, and to push the boundaries of what we can learn from experiments. The stack you would be working with consists of technologies like Spark, Trino, Python, and Airflow.

A typical day:

• Work to build, maintain, optimize and extend complex and large scale data processing pipelines.
• Contribute to Airbnb’s library for flexible and extensible on-demand analysis of experiments.
• Partner with teams across the organization to improve the impact of experimentation across the company. Participate in all phases of software development of the overall platform from architecture/design through implementation, testing, and on-call.
• Work closely with Data Science partners to implement sophisticated statistical methodologies into the platform.

• Participate in experiment reviews to understand how our customers use our infrastructure, identify areas for improvement and learn about features rolling out across the company.

Your expertise:

• 9+ years in a hands-on software engineering role, shipping high quality code to production, especially for high scale, distributed systems, data pipelines, and/or analytical libraries.
• Experience with at least one modern, general programming language (e.g. Python, Java)
• Experience with scientific/statistical computation, especially involving online experimentation
• Experience building software with ergonomic interfaces and great developer experience, especially for technical data users (e.g. data scientists).
• Experience with at least one modern “big data” technology (e.g. Spark, Dataflow)
• Strong SQL skills - you should be able to “go deep” when debugging or optimizing.
• [Nice to have] Experience building frameworks which generate data pipelines at scale.
• [Nice to have] Experience with a distributed stream processing framework (e.g. Flink, Kafka, Dataflow)

Offices: United States

The Community You Will Join:

You will join a team dedicated to driving innovation and optimizing our dynamic Marketplace. As a member of the Marketplace Data Science team, you will tackle challenges at the core of our business, including pricing, supply management, and fee strategies. Collaborating with leaders across the company, you will play a key role in shaping the future of our marketplace.

The Difference You Will Make:

As a Staff Data Scientist, you will be responsible for building data products, inference frameworks, and intelligence to enable the growth of our marketplace. Your work will include:

• Specifying and estimating models to determine the impact of supply and demand on marketplace outcomes
• Delivering data and insights to enable the company’s supply growth efforts
• Providing mentorship to other data scientists and exemplifying a high bar for technical excellence

A Typical Day:

• Crafting models: You will develop models to accurately forecast key marketplace metrics, enabling proactive decision-making and strategic planning.
• Advanced causal inference: Utilizing cutting-edge causal inference techniques, you will quantify the impact of changes in supply and demand on the marketplace, informing targeted improvements and interventions.
• Cross-functional collaboration: You will actively collaborate with teams across product, engineering, and operations to integrate data science insights into initiatives aimed at enhancing supply acquisition, retention, and success.
• Stakeholder engagement: You will engage with stakeholders to understand their business objectives and provide data-driven solutions tailored to these goals.

Your Expertise:

• 9+ years of relevant industry experience and a Master’s degree or PhD in a quantitative field
• Strong fluency in Python or R for hands-on IC work and SQL for advanced data analysis at scale
• Experience with causal inference and machine learning techniques, ideally in a multi-sided platform setting
• Proven ability to succeed in collaborative environments with cross-functional stakeholders and also in independent work environments
• Proven ability to communicate clearly and effectively to audiences of varying technical levels

Offices: United States

The Difference You Will Make:

At CnC, data is foundational to our organization’s success.This role will lead key initiatives to design and build large-scale, distributed data systems - both batch and real-time processing. The data will power machine learning models and unlock new product features. You’ll be at the center of cross-functional collaboration, bridging backend, frontend/client, and machine learning engineering teams.

A Typical Day:

• Shape the team’s long-term vision and roadmap in close collaboration with cross-functional partners across Airbnb
• Build strong relationships with partner engineering teams, including backend, client, data science, analytics, and ML, to drive aligned and impactful outcomes
• Design, develop, and maintain reliable, scalable data pipelines - both batch and real-time - that collect, process, and serve data from diverse sources across Airbnb
• Implement robust offline and online feature building processes to enable faster production of ML products
• Architect and build ML infra and optimize for performance, scalability, and cost-effectiveness
• Mentor and develop engineers on the team, while also contributing to and influencing the broader data engineering community at Airbnb

Your Expertise:

• 9+ years of relevant industry experience with a Bachelor’s and/or Master’s degree in CS/EE, or equivalent experience, or 6+ years of experience with a PhD
• Strong CS fundamentals, and knowledge of architecture and common design patterns
• You’re passionate about being in a product-focused environment where everyone cares deeply about customer impact
• You have experience of running data processing pipelines in production using distributed data processing frameworks like Apache Spark or Flink
• Experience collaborating with client, backend, ml, analytics teams, product and business partners
• Effectively work across team boundaries to establish overarching data architecture, data flow, and provide guidance to individual teams
• Experience working on/with end-to-end Machine Learning products
• Excellent communication skills, both written and verbal

Offices: United States

The Difference You Will Make:

Our team pushes the boundaries of AI and machine learning throughout the search ranking stack, from data pipelines to feature engineering, model innovation, real-time serving, and large-scale experimentation. You’ll work hands-on with diverse data sources—structured, behavioral, image, and text—transforming raw information into intelligent signals that drive relevance and personalized recommendations.

A Typical Day:

• Work with large scale structured and unstructured data, build and continuously improve cutting edge Machine Learning (ML) models for Airbnb product, business and operational use cases.
• 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 machine learning models, drive engineering decisions, and quantify impact.
• Hands-on develop, productionize, and operate ML/AI models and pipelines at scale, including both batch and real-time use cases.
• Leverage third-party and in-house ML/AI tools & infrastructure to develop reusable, highly differentiating and high-performing Machine Learning systems, enable fast model development, low-latency serving and ease of model quality upkeep.
• Example projects include: feature platform, model interpretability, hyperparameter optimization, concept drift detection.

Your Expertise:

• 12+ years of industry experience in applied ML/AI, inclusive MS or PhD in relevant fields.
• Strong programming (Scala / Python / Java / C++ or equivalent) and data engineering skills.
• Deep understanding of ML/AI best practices (e.g. training/serving skew minimization, A/B test, feature engineering, feature/model selection), algorithms (e.g. neural networks/deep learning, optimization) and domains (e.g. natural language processing, computer vision, personalization, search and recommendation, marketplace optimization, anomaly detection).
• Experience with 3 or more of these technologies: Tensorflow, PyTorch, Kubernetes, Spark, Airflow (or equivalent), Kafka (or equivalent), data warehouse (e.g. Hive).
• Industry experience building end-to-end ML/AI infrastructure and/or building and productionizing ML models.
• Exposure to architectural patterns of a large, high-scale software applications (e.g., well-designed APIs, high volume data pipelines, efficient algorithms, models).
• Experience with test driven development, familiar with A/B testing, incremental delivery and deployment.

Offices: United States

The difference you will make

As a Staff Engineer on the Guidance Serving team, you will drive the technical strategy and delivery of advanced online and offline serving systems, enabling seamless and reliable ML model predictions and personalized user experiences. You’ll collaborate cross-functionally with Product, Data Science, and ML Engineering to architect scalable solutions with clear domain boundaries, advance feature engineering pipelines, and continuously enhance the performance, efficiency, and impact of our end-to-end machine learning workflows.

• Design and manage end-to-end data workflows to support the ML engineering lifecycle, focusing on preparing data for model training, tracking data lineage, evolving schemas to adapt to changing needs, and ensuring data integrity and reliability in production.
• Prototype new ideas and influence the serving strategy
• Build and optimize real-time serving systems to deliver low-latency, high-throughput APIs for model predictions and personalized recommendations, ensuring reliable and scalable performance in production environments.
• Collaborate with other product engineers and cross-functional partners to develop new Host pricing functionality and surface model recommendations, insights and analytics
• Contribute to the development of long-term workflow strategies, roadmaps and ML serving development within the Host Pricing organization.
• Mentor and coach team members, providing guidance in ML serving and data engineering best practices and support to enhance their skills and performance.

• Ability to work in areas outside of your usual comfort zone and show motivation for personal growth

Your expertise

• 9+ years of experience with a BS/Masters or 4+ years with a PhD
• You have experience leading teams, setting technical direction, building & launching high-impact models
• You have experience influencing partners as well as other engineering teams
• You exhibit strong ownership and experience building and operating high-scale, distributed systems across the full software life cycle.
• You have excellent communication skills and the ability to work well within a team and across engineering teams.
• Expertise in large-scale distributed data processing frameworks like Presto or Spark.
• Prior experience with the whole lifecycle of productionalization of ML models, including ETL pipelines for data training, feature generation, model evaluation and real-time serving.
• You are a strong problem solver and have solid production debugging skills.

Offices: United States

A Typical Day:

• Define and maintain the product strategy, and roadmap for risk management initiatives focused on fraud detection, defenses, and dispute resolution.
• Align the roadmap with Payments Risk, Payments, and overall Airbnb priorities.
• Set business and platform objectives for each project, ensuring timely delivery and value.
• Continuously optimize risk management approaches to minimize friction for trusted users, enabling seamless experiences that foster revenue growth.
• Work closely with engineering, data science, operations, compliance, legal, and support teams to launch impactful risk-related products and features.
• Expand the use of Gen AI solutions in payments risk, including fraud management and dispute resolution, while leveraging to address emerging threats.

Your Expertise:

• • 10+ years building payments, Payments Risk or risk related products in a product management role within global technology or financial services companies.
  • Prior experience working with Payments Risk including Machine Learning, Transaction Risk. (Fintech experience strongly preferred)
  • A subject matter expert on payments risk with proven track record of launching and scaling risk detection, fraud prevention, or dispute resolution products that balance customer experience
  • Experience leading complex projects, leveraging ML , operations, and signals from external vendors
  • Technical chops with experience as an engineer, data scientist, analyst, or operations
  • Experience integrating Gen AI as solution and delivering business value
  • Thrives in a startup environment: loves dealing with fast pace, changing needs, and limited resources.

Offices: United States