Senior Machine Learning Scientist

Overview

Senior ML Scientist to lead end-to-end ML initiatives in Search Marketing & Tech, delivering production-grade models and roadmaps that drive business impact at scale. You will own problem framing, data design, model development, and deployment, partnering with engineering and product teams. The role emphasizes cross-functional leadership, technical blueprinting, and measurable improvements in customer experiences and performance. This is a chance to shape AI-powered bidding and ranking systems for Expedia’s metasearch ecosystem.

Pay / Benefits

• flexible work arrangements
• supportive environment
• career growth opportunities
• competitive benefits package

Responsibilities

• Own end-to-end ML solutions from problem framing to post-launch iteration
• Define architecture, data contracts, and integration patterns for ML systems
• Lead multi-quarter ML initiatives with engineering, product, and business stakeholders
• Create technical blueprints outlining objectives, constraints, and trade-offs
• Design and implement production-grade models and robust training/evaluation/serving pipelines
• Enhance experimentation strategies and long-horizon metrics to sustain impact
• Collaborate with cross-functional teams to translate ML designs into scalable production systems
• Mentor data and ML scientists and drive adoption of AI best practices
• Lead structured reviews with non-technical audiences to communicate trade-offs

Key requirements

• Master’s or PhD in a quantitative field or equivalent industry experience
• 6+ years (Master’s) or 4+ years (PhD) of hands-on ML experience
• Proven track record leading complex production ML initiatives with measurable impact
• Deep ML expertise in supervised/unsupervised learning and feature engineering
• Strong experimentation and statistics skills including causal inference techniques
• Fluency in Python and core ML libraries (pandas, NumPy, scikit-learn, PyTorch or TensorFlow)
• Solid software engineering practices (clean code, testing, version control, code reviews)
• Proficient with large-scale data: SQL and distributed processing (Spark, Hive)
• Leadership & collaboration skills with ability to influence cross-functional stakeholders
• Experience translating business problems into ML formulations with clear success criteria

• Strong communication, able to present technical concepts clearly to diverse audiences
• Influence and stakeholder alignment across teams
• Problem framing and strategic thinking
• Gradient-boosted trees, deep learning, optimization, RL/bandits
• A/B testing design and causal inference methods (diff-in-diff, IV, matching)
• Experimentation and observability in ML pipelines

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