SlipstreamJobs tracks this role from the company's public career site. Apply directly on the employer's site.
Join Tripadvisor's Experiences R&D Team as a Senior Machine Learning Scientist, where you'll serve as a key technical lead architecting the core discovery engine that powers how millions of users discover and plan travel experiences. You'll independently own and execute ML strategy for major product capabilities—Search, Retrieval, Ranking, or Content AI—bridging state-of-the-art research with production-grade engineering.
Your responsibilities include designing and implementing custom model components that don't exist off-the-shelf, breaking down ambitious research goals into iterative milestones. You'll evaluate the global research landscape to conduct cost-benefit analyses on new architectures, balancing model complexity against inference speed, memory usage, and execution costs. You'll optimize models for production using techniques like quantization and distillation, and implement rigorous validation automation (backtesting, slice-based evaluation) to prevent data leakage and production regressions.
You'll collaborate closely with Engineering Leads to ensure compute and GPU infrastructure supports model requirements, clearly defining model failure modes, edge cases, and confidence thresholds. You'll diagnose complex algorithmic bugs, implement automated checks for silent failures like concept drift or feature distribution shifts, and lead team-level post-mortems. As a career multiplier, you'll formally mentor mid-level and associate ML scientists, reviewing their experimental logic and guiding them through applied ML and production constraints.
Required: Master's or Ph.D. in Computer Science, Machine Learning, Statistics, or a highly quantitative field. 5+ years of industry experience developing, validating, and deploying large-scale ML models in production. Strong practical and theoretical foundation in machine learning, feature engineering, and deep learning. Proven ability to adapt state-of-the-art architectures to solve business problems. Mastery of Python and deep learning frameworks (PyTorch, PyTorch Lightning, or TensorFlow) with familiarity in data versioning and experiment tracking tools.
Desired experience includes next-generation retrieval pipelines, multi-stage ranking systems, Content AI stacks, sequential recommendation systems, Graph Neural Networks, knowledge graphs, multi-modal representation learning, and generative/agentic AI workflows.
