About this role
Salary: £71,000 - 99,000 per year
Requirements: We require a Masters or Ph.D. degree in Computer Science, Machine Learning, Statistics, or a highly quantitative field.We require 5+ years of industry experience developing, validating, and deploying large-scale ML models in production environments.We require a strong practical and theoretical foundation in machine learning techniques, feature engineering, and deep learning paradigms.We require proven ability to tweak, hybridize, and adapt state-of-the-art architectures to solve non-linear business problems.We require mastery of Python and deep learning frameworks such as PyTorch, PyTorch Lightning, or TensorFlow, along with familiarity with data versioning and experiment tracking tools.Experience with multi-task learning (MTL), ranking, Content AI stacks, and Agentic AI is highly desirable. Responsibilities: We act as the technical lead for specific ML projects within our pod.We design and implement custom model components or loss functions that do not exist off the shelf, and break down large research goals into deliverable, iterative milestones.We evaluate the research landscape and conduct cost-benefit analyses on new architectures, balancing model complexity against inference speed, memory usage, and execution costs.We optimize models for production using techniques such as quantization and distillation.We tailor Golden Datasets and leaderboards with minimal supervision and implement rigorous validation automation to prevent data leakage, overfitting, and production regressions.We collaborate closely with Engineering Leads to ensure compute and GPU infrastructure supports model requirements.We define model failure modes, edge cases, and confidence thresholds so engineering partners can build robust fallback systems.We diagnose complex algorithmic bugs and implement automated checks for silent failures such as concept drift or production feature distribution shifts.We lead team-level post-mortems and resolve blocking corrective actions.We mentor mid-level and associate ML scientists, reviewing experimental logic and guiding them through applied ML and production constraints. Technologies: Agentic AIAIMachine LearningPyTorchPythonTensorFlowArchitectSupport More:
We are Tripadvisor Group, connecting people to experiences worth sharing and aiming to be the worlds most trusted source for travel and experiences. Our Tripadvisor Experiences R&D Team is evolving the worlds leading marketplace for travel experiences, with more than 400,000 travel experiences to explore. We offer competitive compensation, annual bonuses, a remote-friendly and flexible work style, donation matching, tuition assistance, a lifestyle benefit, travel perks, an employee assistance program, health benefits, and a generous referral scheme. Our culture is built around putting the traveler first, execution as our edge, and succeeding together. We are committed to an accessible and inclusive candidate experience.
last updated 36 week of 2026