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Senior Staff Software Engineer, Host Pricing & Settings

Own the technical strategy for ML serving and API interface in the Host Pricing org at Airbnb.

Location
Remote - USA
Compensation
Not disclosed
Level
staff
Type
full time · Hybrid

Posted by employer 2 months ago

First seen on Joblaze 1 week ago

Last verified on the company career page 1 day ago

Role intensity

60% hands-on coding

Requirements

Experience
12+ years

Not disclosed in this posting: compensation, visa sponsorship.

Benefits

Remote Work

Joblaze summary

In this role, the Senior Staff Software Engineer will focus on architecting and implementing the technical strategy for machine learning serving and API interfaces within the Host Pricing & Settings team. Key skills include extensive experience in backend engineering, proficiency in languages like Java and Python, and a deep understanding of ML systems design. This position is ideal for seasoned engineers with a strong background in building scalable data infrastructure and leading cross-functional technical initiatives. The team is dedicated to enhancing the tools that empower Airbnb hosts, ensuring they can optimize their pricing strategies effectively.

Joblaze insights

Quick facts

Is the Senior Staff Software Engineer, Host Pricing & Settings role remote?
It's hybrid — Airbnb expects some on-site time in Remote - USA.
How much experience is required?
At least 12 years of relevant experience for this Senior Staff Software Engineer, Host Pricing & Settings role.
Where is the role based?
Airbnb is hiring for this position in Remote - USA.
What's the tech stack?
Joblaze extracted these technologies from the posting: Airflow, Java, Kafka, Kotlin, Python, Scala.
What seniority level is this role?
Airbnb targets staff-level candidates for this position.
Is this full-time or contract?
Full-time for this Senior Staff Software Engineer, Host Pricing & Settings role at Airbnb.

From the original posting

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:

The Host Pricing & Settings team builds the platform and tools that help hosts run their business — with pricing strategies informed by market intelligence, comparable listings, and demand signals. We partner with Search, Listings, Tax, and Payments to ensure our guidance is accurate, timely, and trusted.

Behind every pricing recommendation is a sophisticated ML system undergoing a fundamental rearchitecture. Our north star: a serving infrastructure where training, inference, and evaluation are consistent by design — features from a centralized store, model composition in one place, and backfills available on demand so data scientists and MLEs can evaluate candidates in days, not weeks.

The Difference You Will Make:

As a senior technical individual contributor, you will own the technical strategy for the full Modeling → ML Serving → API interface across the Host Pricing org. Although you will be at one of our highest levels of seniority, all individual contributors at Airbnb are Software Engineers — you are expected to be hands-on and contribute code.

  • Define the architecture and contracts governing how models move from development to production — feature store design, model schema management, online/offline inference consistency, and multi-version support.
  • Lead the buildout of a unified serving stack that eliminates per-model one-off implementations and gives data scientists a turnkey path from training to production.
  • Architect backfill and evaluation infrastructure so the modeling team can simulate production inference over historical data in days, not weeks.
  • Establish domain contracts between Modeling and Serving so each team can move independently with clear, enforced interfaces.

A Typical Day:

  • Review and evolve the ML serving architecture — making tradeoff calls on feature pipeline design, model composition, and API interfaces.
  • Write and review code for feature engineering jobs, feature store configurations, and serving service endpoints.
  • Partner with Data Science, MLE, MLI and core Pricing & Availability systems BE teams to define artifact handoffs and integration contracts.
  • Drive milestone planning across the Host Pricing & Settings org, sequencing work to deliver value incrementally.
  • Mentor engineers through design reviews and hands-on pairing on the hardest infrastructure problems.

Your Expertise:

  • 12+ years in backend or platform engineering, with substantial experience building production ML systems or data-intensive infrastructure.
  • Strong programming skills in Java, Kotlin, Scala, and/or Python.
  • Deep understanding of ML systems design: feature stores, training/serving consistency, model versioning, and online/offline inference pipelines.
  • Experience with high-scale batch and real-time data pipelines (Spark, Airflow, Kafka, or equivalent), including point-in-time correctness for backfills.
  • Expertise with architectural patterns of large, high-scale applications — well-designed APIs, efficient data contracts, multi-tenant serving infrastructure.
  • Proven ability to lead cross-team technical initiatives spanning ML and platform engineering.

Preferred Qualifications:

  • Feature Store Depth: Production experience with Chronon, Tecton, Feast, or equivalent — including online/offline consistency and backfill automation.
  • Model Serving Infrastructure: Experience with model schema management, multi-version support, and model composition frameworks.
  • Domain Contract Design: Track record defining and enforcing technical contracts between ML modeling, MLI, serving teams and/or product surfaces.
  • Evaluation Velocity: Measurable impact improving the speed at which ML teams evaluate candidate models and ship to production.

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. 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.

Reasonable Accommodations: We are committed to providing reasonable accommodations throughout the recruitment process for applicants with disabilities. If you need assistance, or an accommodation, please let your recruiter know once you are contacted about a role.

A Note on Recruiting Scams: Scammers sometimes pose as Airbnb recruiters to get money or personal information from candidates. A few things that will always be true for Airbnb’s hiring process: our open roles are posted on Airbnb’s Career’s Page at careers.airbnb.com, and our recruiters correspond only from @airbnb.com or @ext.airbnb.com email addresses. Our recruiters will never ask for your Social Security number, bank account details, passport, or payment app information while you are interviewing. We’ll also never ask you to pay a fee, send money, deposit or cash a check, or purchase work-related equipment (such as a company laptop) during the interview process. We encourage candidates to remain vigilant of these recruiting scams and not share sensitive information if you do not believe an individual is actually affiliated with Airbnb.

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