- Company Name
- Expedia Group
- Job Title
- Machine Learning Scientist II
- Job Description
-
**Job Title:**
Machine Learning Scientist II
**Role Summary:**
Applied research scientist focused on designing, building, and deploying ranking models that select and order property images and reviews for a large travel portfolio. Models are production‑ready, evaluated via A/B testing, and directly influence business metrics. Works cross‑functionally with product managers, data scientists, and engineering teams.
**Expectations:**
- Deliver end‑to‑end ML solutions that meet product objectives.
- Translate business problems into quantifiable ML opportunities.
- Maintain high code quality, reproducibility, and documentation.
- Communicate results clearly to technical and non‑technical stakeholders.
- Stay current with advances in machine learning and generative AI.
**Key Responsibilities:**
- Collaborate with product management to define ML problems and scope solutions.
- Conduct exploratory data analysis, feature engineering, and model experimentation.
- Build and optimize algorithms using Python and deep‑learning frameworks.
- Partner with data and software engineering to deploy models into production pipelines.
- Develop a deep understanding of the data and ML infrastructure (Spark, Databricks, etc.).
- Document technical details, maintain versioned notebooks, and create reproducible workflows.
- Present findings and performance metrics to product, engineering, and leadership teams.
- Brainstorm and share ideas with teammates and across the organization.
- Continuously learn new techniques, tools, and frameworks to advance the team’s capabilities.
**Required Skills:**
- Proficient in Python, TensorFlow or PyTorch, SQL and data manipulation libraries.
- Experience with distributed computing tools (Spark, Databricks) and large‑scale data pipelines.
- Strong foundation in machine learning theory, statistics, and experimentation (A/B testing, feature importance, uncertainty estimation).
- Ability to write efficient, readable, and well‑tested code; familiarity with version control (Git).
- Demonstrated ability to deploy production‑ready ML models and maintain them.
- Strong communication and presentation skills.
**Required Education & Certifications:**
- Master’s degree or Ph.D. in Computer Science, Statistics, Mathematics, Engineering, or a related technical field, **or** equivalent professional experience.
**Preferred Qualifications (not mandatory):**
- Experience with ranking systems, large‑language models, fine‑tuning, and efficient deployment.
- Familiarity with ML platforms such as Databricks, cloud services (AWS, GCP, Azure), Docker, and orchestration tools (Airflow, Flyte).
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