Staff/Principal Machine Learning Scientist - Ranking & Retrieval

Requirements

• Education: Ph.D. or Master’s degree in Computer Science, Machine Learning, Statistics, or a highly quantitative field.
• Experience: 8+ years of industry experience developing and deploying large-scale ML models in a production environment.
• Core Technical Expertise:
  • SOTA Retrieval & Ranking: Practical experience with Multi-Task Learning (MTL), Multi-gate Mixture-of-Experts (MMoE), or similar architectures.
  • Sequential & Temporal Modeling: Hands-on experience building sequential recommendation systems.
  • Advanced Representation Learning: Deep understanding of embedding generation, deep semantic retrieval, and multi-modal representation learning.
• Technical Stack: Mastery of Python, TensorFlow, PyTorch, distributed computing, and cloud infrastructure.

Nice to Haves

• Graph Neural Networks (GNNs): Strong experience applying GNNs, knowledge graphs, or graph embeddings in complex relations mapping.
• Agentic AI & Generative AI: Familiarity with Agentic AI frameworks, LLM-driven reasoning, or autonomous planning agents.
• Experience working in E-commerce, Travel Tech, or Two-Sided Marketplaces.
• Strong track record of academic or industry contributions, including publications in top-tier AI/IR conferences or open-source ML contributions.

What You'll Be Doing

• Technical Leadership & Execution: Drive the technical roadmap for Search, Retrieval, Ranking, and Recommendation systems within the Trips vertical.
• Advanced Algorithm Innovation: Design, prototype, and scale next-generation recommendation and ranking models.
• System Architecture & Scalability: Oversee the deployment of low-latency, high-throughput retrieval and ranking pipelines.
• Cross-Functional Collaboration: Partner closely with Product Managers, Engineering Leads, and Data Science peers.
• Talent Multiplier: Mentor and coach senior and mid-level ML scientists.

Perks and Benefits

• Competitive compensation packages, including base salary and annual bonuses.
• Flexible work schedule with a remote-friendly approach to collaboration.
• Donation matching, tuition assistance, lifestyle benefit, and travel perks.
• Employee assistance program, health benefits, and generous referral scheme.