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Airbnb Machine Learning Jobs (NOW HIRING)

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AI Engineer

San Francisco, CA · On-site

... 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 ...

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AI Engineer

San Francisco, CA

... 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 ...

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AI Engineer

San Francisco, CA · On-site

... 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

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 ...

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 ...

EvolutionIQ

Full Stack Engineer - Tech Lead

Manhattan, NY · On-site +1

... Airbnb, Pinterest, Shopify) and Foundation Capital (Lending Club, CoverWallet, Netflix) and we have ... The applications you'll be building will deliver machine learning insights and workflows to our ...

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Showing results 41-60

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 Aug 9, 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.

What are the key skills and qualifications needed to thrive as a machine learning engineer at Airbnb?

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.

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 August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 24% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $42,584 per year, or $20.5 per hour.

Research Engineer - Reinforcement Learning

Prime Intellect

San Francisco, CA • On-site, Remote

$350K/yr

Full-time

Re-posted 16 days ago

Job description

Own Your Intelligence
Prime Intellect is building the open superintelligence stack: the infrastructure frontier AI labs build internally, made available to every ambitious AI team.
Our platform, Lab, unifies compute, environments, evaluations, secure sandboxes, high-performance training, and deployment into one full-stack system for post-training at frontier scale - from SFT and RL to tool use, agent workflows, and continuously improving production models. We are building open frontier AI: open-source models trained end to end for long-horizon tasks like autonomous research, and the full-stack platform our own research team uses to build them. The next generation of AI companies, enterprises, and research teams do not just need more GPUs. They need the ability to turn their own workflows, tools, data, and feedback loops into superintelligence they own.
Prime Intellect has raised $150M in total funding from Founders Fund, Radical Ventures, NVIDIA, and exceptional AI, infrastructure, and enterprise operators - including Andrej Karpathy, Dwarkesh Patel, and leaders and founders from Ramp, Perplexity, Harvey, Mercor, Zapier, Datadog, Cognition, OpenAI, Thinking Machines, Together AI, SemiAnalysis, LangChain, Browserbase, Cloudflare, Sierra, Databricks, Airbnb, OpenRouter, Standard Intelligence, Fleet, Core Auto, and more. We are looking for people who want to build at the intersection of frontier research, real infrastructure, and go-to-market for a category that does not fully exist yet.
Responsibilities
  • Lead and participate in novel research to build a massive scale synthetic data generation pipeline and orchestration solution
  • Optimize the performance, cost, and resource utilization of AI inference workloads by leveraging the most recent advances for compute & memory optimization techniques.
  • Contribute to the development of our open-source libraries and frameworks for synthetic data generation and distributed RL frameworks.
  • Publish research in top-tier AI conferences such as ICML & NeurIPS.
  • Distill highly technical project outcomes in layman approachable technical blogs to our customers and developers.
  • Stay up-to-date with the latest advancements in AI/ML infrastructure and tools, synthetic data gen research and proactively identify opportunities to enhance our platform's capabilities and user experience.
Requirements
  • Strong background in AI/ML engineering, with extensive experience in designing and implementing end-to-end pipelines for the inference or training of large-scale AI models.
  • Deep expertise in distributed inference techniques and frameworks (e.g. vllm, sglang) for optimizing the performance and scalability of AI workloads.
  • Solid understanding of MLOps best practices, including model versioning, experiment tracking, and continuous integration/deployment (CI/CD) pipelines.
  • Passion for advancing the state-of-the-art in reasoning and democratizing access to AI capabilities for researchers, developers, and businesses worldwide.
  • If you're not familiar with these, but feel like that you can contribute to our mission and you're a high-energy person, get familiar with these resources (here, here and here) and please reach out!
Benefits & Perks
  • Cash Compensation Range of $150-350k, including equity incentives, aligning your success with the growth and impact of Prime Intellect.
  • Flexible work arrangements, with the option to work remotely or in-person at our offices in San Francisco.
  • Visa sponsorship and relocation assistance for international candidates.
  • Quarterly team off-sites, hackathons, conferences and learning opportunities.
  • Opportunity to work with a talented, hard-working and mission-driven team, united by a shared passion for leveraging technology to accelerate science and AI.

If you're excited about the opportunity to build the foundation for the future of decentralized AI and create a platform that empowers developers and researchers to push the boundaries of what's possible, we'd love to hear from you.

Apply