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Airbnb Machine Learning Jobs (NOW HIRING)

Match Point Solutions

Resident Engineer

Pleasanton, CA · On-site

$60 - $65/hr

We provide technology solutions to various clients like Uber, Robinhood, Netflix, Airbnb, Google ... Data Science & AI : Experience or hands-on exposure to data science, machine learning, and ...

Amazon

Software Development Manager - Compiler

Cupertino, CA · On-site

$152K - $201K/yr

AWS Machine Learning accelerators are at the forefront of AWS innovation. The Inferentia chip ... AirBnB, Autodesk, Amazon Alexa, and more customers in various other segments. The Team: The Amazon ...

Zip

Technical Sourcer

Seattle, WA · On-site +1

$125K - $190K/yr

Zip's team includes product leaders from Apple, Airbnb, and Meta, as well as former procurement ... Security Engineering, Machine Learning, Infrastructure, SRE, DevOps, and AI Engineers.

Collate

AI Engineer

San Francisco, CA · On-site

$150K - $350K/yr

... AirBnB, Hippocratic AI, and Grail, and 40% of our team are former founders. We're an elite team ... You'll work at the intersection of machine learning, software engineering, and product -- turning ...

Landing

Senior Director of Pricing

Enhance and scale our machine learning-driven pricing model. * Develop and deploy dynamic pricing ... Experience with OTA pricing or channel management (Airbnb, Expedia, Booking.com). * Familiarity ...

Collate

AI Engineer

San Francisco, CA

$150K - $350K/yr

... AirBnB, Hippocratic AI, and Grail, and 40% of our team are former founders. We're an elite team ... You'll work at the intersection of machine learning, software engineering, and product - turning ...

Collate

AI Engineer

San Francisco, CA · On-site

$150K - $350K/yr

... AirBnB, Hippocratic AI, and Grail, and 40% of our team are former founders. We're an elite team ... You'll work at the intersection of machine learning, software engineering, and product - turning ...

Vendelux Inc

Senior AI Engineer

New York, NY · On-site +1

$114K - $157K/yr

... Compass, Airbnb, Forter and beyond. Key Responsibilities * Applied AI Innovation: Research and ... Strong grasp of fundamental data science and machine learning techniques, with the ability to ...

Vendelux Inc

Staff AI Engineer

New York, NY · On-site

... Compass, Airbnb, Forter and beyond. Key Responsibilities * Applied AI Innovation: Research and ... Strong grasp of fundamental data science and machine learning techniques, with the ability to ...

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Showing results 1-20

All JobsAirbnb Machine Learning Jobs

Airbnb Machine Learning information

See salary details

$25.5K

$42.6K

$88K

How much do airbnb machine learning jobs pay per year?

As of Jul 14, 2026, the average yearly pay for airbnb machine learning in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.

How much do machine learning engineers make at Airbnb?

Machine learning engineers at Airbnb typically earn between $120,000 and $180,000 annually, depending on experience, location, and skill set. Compensation may also include bonuses and stock options, with roles often requiring proficiency in Python, TensorFlow, or similar tools.

Is it hard to get hired by Airbnb?

Getting hired for an Airbnb Machine Learning role can be competitive, often requiring strong technical skills in machine learning, data analysis, and programming languages like Python or R. Candidates typically go through multiple interview rounds that assess technical knowledge, problem-solving ability, and relevant experience. Having a solid portfolio or experience with cloud platforms and machine learning tools can improve chances of success.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer at Airbnb, and why are they important?

To thrive as a Machine Learning Engineer at Airbnb, you need a strong background in computer science, statistics, and machine learning algorithms, often supported by a degree in a related field and experience with real-world data projects. Proficiency in programming languages like Python or Scala, familiarity with frameworks such as TensorFlow or PyTorch, and experience with cloud platforms and data pipelines are typically required. Strong problem-solving skills, collaboration, and effective communication set top performers apart in this role. These skills enable engineers to build robust, scalable models that drive product innovation and enhance Airbnb's user experience.

What are some of the most common challenges faced by machine learning engineers at Airbnb when deploying models to production?

Machine learning engineers at Airbnb often encounter challenges related to ensuring data quality and consistency between offline training datasets and real-time production data. Additionally, integrating models with large-scale systems while maintaining low latency and high reliability can be complex. Engineers must also collaborate closely with data scientists, product managers, and software engineers to align model outputs with business objectives and user experience. Ongoing monitoring and rapid iteration are essential to adapt to changing user behavior and platform needs.

What is the difference between Airbnb Machine Learning vs Airbnb Data Scientist?

AspectAirbnb Machine LearningAirbnb Data Scientist
Required CredentialsDegree in Computer Science, Data Science, or related field; experience in ML algorithmsDegree in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentFocus on developing ML models, algorithms, and automation toolsAnalyze data, generate insights, and support decision-making
Employer & Industry UsageTech-driven, product-focused roles within AirbnbData analysis and strategic insights for Airbnb operations
Common Search & ComparisonOften compared for technical ML skillsCompared for data analysis and business insights

Airbnb Machine Learning specialists focus on building and deploying machine learning models to enhance platform features, while Airbnb Data Scientists analyze data to inform business decisions. Both roles require strong technical skills, but their core responsibilities differ in application and focus within Airbnb's tech ecosystem.

Which 3 jobs will survive AI?

In the context of Airbnb machine learning roles, jobs that involve complex problem-solving, creative tasks, and human interaction are more likely to survive AI automation. These include data scientists, machine learning engineers, and customer experience specialists, as they require advanced analytical skills, domain expertise, and emotional intelligence. Continuous learning and proficiency with AI tools and programming languages like Python or R can also enhance job security in this field.

How does Airbnb use machine learning?

Airbnb machine learning roles involve developing algorithms to improve search rankings, personalize recommendations, and detect fraudulent activity. These roles require skills in data analysis, model development, and tools like Python and TensorFlow. Machine learning helps enhance user experience and platform security.

What does a Machine Learning Engineer do at Airbnb?

A Machine Learning Engineer at Airbnb develops and implements machine learning models to solve complex business problems, such as optimizing search results, personalizing recommendations, detecting fraud, and improving user experiences. They work closely with data scientists, product managers, and software engineers to design scalable systems that can process large amounts of data. Their role often involves data preprocessing, feature engineering, model training, evaluation, and deployment into production environments.
More about Airbnb Machine Learning jobs
What states have the most Airbnb Machine Learning jobs? States with the most job openings for Airbnb Machine Learning jobs include:
What job categories do people searching Airbnb Machine Learning jobs look for? The top searched job categories for Airbnb Machine Learning jobs are:
Airbnb Machine Learning jobs near you
Infographic showing various Airbnb Machine Learning job openings in the United States as of July 2026, with employment types broken down into 32% Full Time, 2% Part Time, 4% Contract, 51% Nights, and 11% Summer. Highlights an 77% Physical, 1% Hybrid, and 22% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.
Senior Applied AI/ML Scientist - Ads Bidding

Senior Applied AI/ML Scientist - Ads Bidding

Faire

San Francisco, CA • On-site

$196K - $269K/yr

Other

Re-posted 13 days ago

Job description

About this Role

The Ads Data team is building the next generation of advertising products for the wholesale industry. As a key member of this team, you'll shape the future of our ads marketplace and auction system at Faire-spanning auction design, bidding strategy, pacing, pricing, and budget optimization. Our in-house stack gives us unique end-to-end ownership, and our first-party conversion data allows us to train highly effective models and optimize for real, business-critical outcomes on behalf of our brands.

This is a rare opportunity to be an early contributor to a fast-growing team in an incredibly strategic area of the business. Ads is a major company priority and you'll have a massive impact in shaping the platform that connects independent retailers and brands. You'll work closely with engineers, product managers, and designers to launch and iterate on systems that are not just technically sophisticated, but also directly drive improvements to the bottom line for both brands and Faire.

What You'll Do

  • Own the end-to-end development of ML models across the ads bidding stack-from problem framing, solution design, modeling, and implementation to deployment, experimentation, and impact measurement.
  • Build best-in-class models and algorithms for auction optimization, bid shading and bid multipliers, budget allocation, pacing, and advertiser ROI/ROAS optimization-drawing from marketplace optimization and experimentation best practices.
  • Define and improve bidding and pacing strategies that balance advertiser performance, marketplace health, and platform economics (e.g., spend smoothing, delivery guarantees, seasonal demand, and inventory constraints).
  • As an early member of the Ads Data team, help define its roadmap and technical culture, leveraging deep product intuition to shape what ads at Faire *should* be-not just how they're built.
  • Work in a fast-paced, collaborative environment with team members who've shipped ML at top tech companies (e.g. Uber, Airbnb, Meta, Amazon, Pinterest).

Qualifications

  • 4+ years of industry experience using machine learning to solve real-world problems, ideally in Ads, Marketplace Optimization, Pricing, Auctions, or a related large-scale production domain.
  • Demonstrated ownership of the full ML lifecycle: from scoping and design through training, deployment, A/B testing, and iteration.
  • Strong programming skills.
  • Experience with relational databases and SQL.
  • The ability to contribute to team strategy and to lead model development without supervision.
  • Strong communication skills and the ability to work with others in a closely collaborative team environment.

Great to Haves

  • Highly recommended: Master's or PhD in Computer Science, Statistics, or related STEM fields
  • Ability to quickly implement state of the art algorithms from an academic paper

Salary Range

San Francisco: the pay range for this role is $196,000 to $269,500 per year.

This role will also be eligible for equity and benefits. Actual base pay will be determined based on permissible factors such as transferable skills, work experience, market demands, and primary work location. The base pay range provided is subject to change and may be modified in the future.

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