Principal Machine Learning Scientist
New
T
TripadvisorTravel technology
Listing locations: UKFull-TimePrincipal
SalaryBase salary and annual bonuses
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Job Details
- Experience
- 8+ years of industry experience
- Required Skills
- PythonMachine LearningPyTorchSparkTensorflow
Requirements
- Ph.D. or master’s degree in computer science, machine learning, statistics, or a highly quantitative field.
- 8+ years of industry experience developing and deploying large-scale machine learning models in production.
- Track record of shipping systems at the scale of millions of active users.
- Practical experience with Multi-Task Learning (MTL), Multi-gate Mixture-of-Experts (MMoE), or similar multi-objective architectures.
- Hands-on experience building sequential recommendation systems.
- Deep understanding of embedding generation, deep semantic retrieval, and multimodal representation learning.
- Mastery of Python and deep learning frameworks such as TensorFlow or PyTorch.
- Hands-on experience with distributed computing such as Spark or Ray, and cloud infrastructure such as AWS or GCP.
- Strong experience applying graph neural networks, knowledge graphs, or graph embeddings is desired.
- Familiarity with Agentic AI frameworks, LLM-driven reasoning, or autonomous planning agents is desired.
- Experience in e-commerce, travel technology, or two-sided marketplaces is desired.
Responsibilities
- Drive the technical roadmap for search, retrieval, ranking, and recommendation systems within the Trips vertical.
- Translate business goals into machine learning architectures and scalable production systems.
- Design, prototype, and scale recommendation and ranking models.
- Oversee deployment of low-latency, high-throughput retrieval and ranking pipelines.
- Partner with product managers, engineering leads, and data science peers to optimize business objectives.
- Serve as the primary technical authority for machine learning initiatives within the Trips vertical.
- Mentor and coach senior and mid-level machine learning scientists.
- Drive best practices for MLOps, A/B testing, data privacy, and code quality.
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