Expedia Group

Expedia Group

Machine Learning Engineer III

USA - California - San Jose, USA · Mid

No sponsorship$158k-$221kDetected 9 hours ago
PythonDistributed SystemsSQLDatabricksAWSCloud PlatformsMachine LearningTensorFlowPyTorchSparkData EngineeringData ScienceNLPMLOpsA/B TestingRecruitingCollaborationMentoring

Stay score

odds of building a lasting career here

64Sponsors, lottery-bound
Cap-exempt (no lottery)0
Sponsors this role100
Entry-level history0
PERM / green-card track0
Lottery odds (Level IV)94
Fits your clock70

Sponsors, but it's cap-subject — you still face the weighted lottery (~61% per draw at Level IV). Good if you win; have a cap-exempt backup on your list.

Lottery odds assume a STEM candidate.

Personalize to your clock →

H-1B wage level

the lottery is wage-weighted — each level is one more entry

Level III · 3×
Level I$94,3701 entry
Level II$123,8432 entries
Level III$153,3173 entries
Level IV$182,7904 entries

$25,290 more$182,790 — moves this role to Level IV and 4 lottery entries. That figure is inside the range the employer already advertised.

Based on the DOL prevailing wage for this occupation and worksite, a base salary of $182,790 would place this position at wage Level IV. That figure is within the posted range, and I'd like to target it. This role classifies under "Software Developers" for prevailing-wage purposes.

DOL prevailing wage, 2026-27 wage year · Software Developers (15-1252) · Bakersfield-Delano, CA. Wage level is derived by USCIS from the offered wage, occupation and worksite; the occupation shown is inferred from the job title.

Employer immigration record

from this employer's Department of Labor filings

Green-card filing pattern in this occupation

Context, not a finding about this posting: of this employer's 47 green-card filings in this occupation, 100% were for a worker who already held the job.

Green-card intent detected

Expedia, Inc. obtained a prevailing wage determination for Software Developers in Austin, TEXAS on 2026-06-17. No matching green-card filing appears in our data yet. The determination expires in 9 days (2026-09-14), and a green-card filing must follow before then or the employer starts over.

Green-card follow-through: 75%

Of 16 labor certifications old enough to have been used, 4 expired without the employer filing the next step. Median time from filing to decision: 451 days.100% of their filings were for a worker who already held the job.Only certifications past the 180-day window are counted — recent ones cannot have expired yet.

Files H-1B transfers

83 transfer filings in the last year, covering 83 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

Community outcomes

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About the role

  • Model Deployment & Integration: Operationalize ML models developed by ML scientists, integrating them with ad delivery, bidding, ranking, and campaign management systems
  • Advertising at Scale: Enable low-latency inference and real-time decisioning for advertising systems serving millions of users across multiple brands and surfaces
  • Monitoring & Optimization: Ensure reliability, scalability, and performance of ML-powered ad systems through robust monitoring, alerting, and continuous optimization

Responsibilities

  • Design and implement scalable batch and real-time ML pipelines to support advertising delivery and optimization across channels
  • Build and maintain reliable data pipelines to ingest, process, and transform large-scale ad impressions, clicks, and conversion data
  • Partner closely with ads product, engineering, analytics, and business teams to align ML solutions with marketplace and revenue goals
  • Develop reusable components, APIs, and orchestration workflows to support experimentation, deployment, and rapid iteration in ad systems
  • As a global travel company powered by passionate people, trusted partnerships, and leading technology, we connect travelers, partners, and advertisers through our consumer brands, B2B network, and travel advertising business.

Requirements

  • Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or a related quantitative field
  • Proficiency in Python and familiarity with ML frameworks such as PyTorch or TensorFlow
  • Experience working with data pipelines and large datasets, using tools such as Spark, SQL, or similar

Nice to have

  • Experience contributing to production ML systems, including model training, evaluation, or inference pipelines
  • Familiarity with distributed data processing (Spark, Databricks) and cloud environments (AWS preferred)
  • Exposure to MLOps concepts, such as model deployment, monitoring, or retraining workflows
  • Basic familiarity with real-time or near-real-time ML systems
  • Background or interest in ads, marketplaces, e-commerce, or travel platforms
  • The total cash range for this position in San Jose is $157,500.00 to $220,500.00.
  • Employees in this role have the potential to increase their pay up to $233,500.00, which is the top of the range, based on ongoing, demonstrated, and sustained performance in the role.
  • Pay ranges may be modified in the future.

Compensation

  • $158k-$221k

Company info

  • We are seeking a Machine Learning Engineer III to join our Advertising Technology team, where we build and operate large-scale batch and real-time ML systems that power pricing, inventory optimization, ranking, and trust & safety across the ad platform.
  • This role sits at the intersection of machine learning, distributed systems, and MLOps, directly influencing how models are designed, deployed, and operated in production at scale.
  • You will work closely with Software Engineering, Data Science, Product, and Platform teams to translate modeling ideas into reliable, observable, and scalable ML systems, while setting technical direction, raising engineering standards, and mentoring others as the platform and business grow.
  • In this role, you will:
  • ML Infrastructure & Pipelines: Design and implement scalable batch and real-time ML pipelines to support advertising delivery and optimization across channels
  • Data Engineering: Build and maintain reliable data pipelines to ingest, process, and transform large-scale ad impressions, clicks, and conversion data
  • Cross-Functional Collaboration: Partner closely with ads product, engineering, analytics, and business teams to align ML solutions with marketplace and revenue goals
  • Tooling & Automation: Develop reusable components, APIs, and orchestration workflows to support experimentation, deployment, and rapid iteration in ad systems
  • Minimum Qualifications
  • 4+ years of industry experience working with machine learning or data-driven systems

Equal opportunity

  • Expedia is committed to creating an inclusive work environment with a diverse workforce.
  • This employer participates in E-Verify.
  • The employer will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee's I-9 to confirm work authorization.
  • All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, veteran status, or any other characteristic protected by law.

Visa & Work Authorization

  • The employer will provide the Social Security Administration (SSA) and, if necessary, the Department of Homeland Security (DHS) with information from each new employee's I-9 to confirm work authorization.

This listing is sourced directly from Expedia Group's careers page and normalized into a canonical job model.