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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in building and optimizing Machine Learning models and infrastructure, with a strong focus on end-to-end ranking algorithms and data engineering. Proficient in collaborating across teams to drive impactful engineering decisions and enhance model performance.
Highest-signal resume keywords
Applied Machine Learning ExperienceProgramming Skills in Scala, Python, Java, C++Machine Learning Best PracticesExperience with TensorFlow, PyTorch, KubernetesEnd-to-End Machine Learning Infrastructure
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningData EngineeringFeature EngineeringHyperparameter OptimizationNatural Language ProcessingComputer VisionA/B TestingModel InterpretabilityAnomaly DetectionMarketplace Optimization
Soft Skills
CollaborationDecision-MakingQuantitative Analysis
Tools & Technologies
TensorFlowPyTorchKubernetesSparkAirflowKafkaHive
Industry Keywords
End-to-End Ranking AlgorithmsLarge-Scale DataReal-Time Use CasesHigh-Volume Data PipelinesTest-Driven Development
Tech Stack
Tools & technologiesAirflowJavaKafkaKubernetesPythonPyTorchScalaSparkTensorflowC++
About the role
Key responsibilities & impact- Lead work on critical, impactful projects focused on end-to-end ranking algorithms and ecosystems for optimizing multiple business objectives
- Build and continuously improve cutting-edge Machine Learning models using large-scale structured and unstructured data
- Collaborate with software engineers, product managers, operations, and data scientists to identify business-impact opportunities and refine and prioritize model requirements
- Drive engineering decisions and quantify impact
- Develop, productionize, and operate Machine Learning models and pipelines at scale for batch and real-time use cases
- Leverage third-party and in-house Machine Learning tools and infrastructure to build reusable, high-performing systems
- Enable fast model development, low-latency serving, and easier model-quality upkeep
- Work on projects such as feature platforms, model interpretability, hyperparameter optimization, and concept drift detection
- Collaborate across Airbnb to develop ranking solutions supporting a healthy marketplace for hosts and guests
Requirements
What you’ll need- 5+ years of industry experience in applied Machine Learning, inclusive of an MS or PhD in relevant fields
- Strong programming and data engineering skills in Scala, Python, Java, C++, or equivalent
- Deep understanding of Machine Learning best practices, including training/serving skew minimization, A/B testing, feature engineering, and feature/model selection
- Knowledge of neural networks/deep learning and optimization
- Knowledge of natural language processing, computer vision, personalization, search and recommendation, marketplace optimization, or anomaly detection
- Experience with 3 or more of TensorFlow, PyTorch, Kubernetes, Spark, Airflow or equivalent, Kafka or equivalent, and data warehouses such as Hive
- Industry experience building end-to-end Machine Learning infrastructure and/or building and productionizing Machine Learning models
- Exposure to architectural patterns of large, high-scale software applications, including well-designed APIs, high-volume data pipelines, and efficient algorithms/models
- Experience with test-driven development, A/B testing, incremental delivery, and deployment
- Must live in a state where Airbnb, Inc. has a registered entity
Benefits
Comp & perks- Bonus eligibility
- Equity eligibility
- Benefits
- Employee Travel Credits
- Remote work eligibility
- Occasional work at an Airbnb office or attendance at offsites, as agreed with the manager
- Reasonable accommodations throughout the recruitment process for applicants with disabilities