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Senior Machine Learning EngineerPowerToFly • San Jose, Arizona, United States
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Senior Machine Learning Engineer

PowerToFly
  • US
    San Jose, Arizona, United States
  • US
    San Jose, Arizona, United States
Jetzt Bewerben

Über

Senior ML/Gen AI Engineer Introduction to the Team Expedia Technology teams partner with Product teams to create innovative products, services, and tools to deliver high‑quality experiences. A platform powered by data and machine learning provides secure, differentiated, personalized experiences.
We are the Strategic Partnerships & Affiliates team building a next‑generation B2B partnership platform serving a wide range of demand partners. We need engineers with an entrepreneurial approach who love challenges and problem solving.
Responsibilities
Collaborate closely with ML Scientists to productize and scale ML models, from experimentation to robust production systems
Design, build, and own large‑scale, distributed machine learning systems for training, deployment, inference, and monitoring
Lead design discussions and architecture reviews; drive high‑impact engineering decisions for ML platforms and applications
Mentor and coach junior engineers and peers on best practices in ML engineering, system design, and code quality
Develop and maintain reusable components, libraries, and tools to accelerate ML development lifecycle
Proactively identify areas for improvement in model performance, pipeline efficiency, data quality, or platform capabilities
Ensure scalability, observability, and fault‑tolerance across all components of the ML stack
Promote engineering excellence by advocating for best practices in testing, CI/CD, infrastructure‑as‑code, and monitoring
Partner with stakeholders across Data Engineering, Product, Marketing, and Platform teams to align solutions with business goals
Stay up to date on advancements in MLOps, ML frameworks, distributed systems, and apply learnings to improve systems and processes
Minimum Qualifications
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
8+ years of experience in software/ML engineering with a proven track record of delivering ML solutions at scale
Strong programming skills in modern languages such as Python, Scala, or Java
Deep experience in building and maintaining production‑grade ML pipelines and infrastructure
Expertise in MLOps practices, including model lifecycle management, versioning, monitoring, and CI/CD for ML
Experience with big data ecosystems (e.g., Spark, Hive, Databricks, Delta Lake) and streaming technologies
Proficient in working with ML frameworks like TensorFlow, PyTorch, XGBoost, or similar
Experience working in cloud‑based environments (AWS, GCP, or Azure) and with infrastructure‑as‑code tools
Hands‑on experience with orchestration tools like Flyte, Airflow, Kubeflow, etc.
Proficient in containerization and orchestration technologies like Docker and Kubernetes
Preferred Qualifications
Familiarity with advanced ML techniques, including deep learning, NLP, recommendation systems, and generative AI
Experience designing or implementing multi‑agent architectures for autonomous collaboration and decision‑making
Understanding of agent planning, memory, tool use, and self‑reflection mechanisms
Experience building basic ML models
Experience with automated testing across different layers (unit, integration, functional)
Compensation San Jose salary range: $199,000.00–$278,500.00, potential up to $318,500.00. Seattle salary range: $184,500.00–$258,000.00, potential up to $295,000.00.
Equal Employment Opportunity Statement Expedia is committed to creating an inclusive work environment with a diverse workforce. 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. 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.
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  • San Jose, Arizona, United States

Sprachkenntnisse

  • English
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