Tripadvisor on cord

Tripadvisor

Principal Machine Learning Scientist

External position
London, UK
Hiring internally for Tripadvisor?
Travel · Marketplace
Your future shaping programmatic media partner.
Posted
a month ago
Checked
cord regularly checks that external positions are still open
9 hours ago

Skills & Experience

Job roles: Machine Learning Engineer
Experience level: Senior, Lead, Leadership
Core skills considered: Artificial Intelligence, Machine Learning, Deep Learning, Python, Tensorflow
Other skills considered: PyTorch, AWS, GCP, Data Pipelines, Data Modeling

Logistics

Base salary: Undisclosed
Some companies on cord are unable to disclose salaries publicly due to internal company policies. Message the company for salary information.
Employment type: Permanent
Remote working: Hybrid
Visa sponsorship: Not available

Job Description

As a Principal Machine Learning Scientist, you will be the technical anchor for our core discovery engine. You will lead the machine learning strategy and execution that powers how millions of users search for, discover, and organize their complex travel itineraries. This is a high-impact role bridging the gap between cutting-edge AI research and production-grade engineering, directly influencing multi-objective business outcomes like user engagement, booking conversion, etc.

You will tackle complex, ambiguous problems at the intersection of deep multi-task ranking, sequential user modeling, and graph-based travel recommendations. If you are passionate about building state-of-the-art AI systems and mentoring a high-performing team of scientists, this role is for you


What You'll Do

  • Drive the technical roadmap for Search, Retrieval, Ranking, and Recommendation systems within the Trips vertical. Translate high-level business goals into concrete ML architectures and scalable production systems.
  • Design, prototype, and scale next-generation recommendation and ranking models. Solve complex, non-linear travel journeys by utilizing sequential recommenders, representation learning, and deep multi-objective frameworks.
  • Oversee the deployment of low-latency, high-throughput retrieval and ranking pipelines (e.g., multi-stage retrieval, vector search) capable of processing billions of travel data points (reviews, photos, bookings, user intent) in real-time.
  • Partner closely with Product Managers, Engineering Leads, and Data Science peers to optimize multi-task business objectives simultaneously. Act as the primary technical authority for ML initiatives within the Trips vertical.
  • Mentor and coach senior and mid-level ML scientists. Foster a culture of technical excellence, driving best practices for MLOps, rigorous A/B testing, data privacy, and code quality.

Skills & Experience:

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, with a proven track record of shipping systems at the scale of millions of active users.

Core Technical Expertise: Deep theoretical and practical knowledge in the following areas:

  • SOTA Retrieval & Ranking: Practical experience with Multi-Task Learning (MTL), Multi-gate Mixture-of-Experts (MMoE), or similar architectures optimized for multi-objective optimization.
  • Sequential & Temporal Modeling: Hands-on experience building sequential recommendation systems that capture real-time user session dynamics and long-term historical preferences.
  • Advanced Representation Learning: Deep understanding of embedding generation, deep semantic retrieval, and multi-modal representation learning.

Technical Stack: Mastery of Python and deep learning frameworks (TensorFlow, PyTorch) alongside hands-on experience with distributed computing (Spark, Ray) and cloud infrastructure (AWS/GCP).

Desired:

  • Graph Neural Networks (GNNs): Strong experience applying GNNs, knowledge graphs, or graph embeddings to map complex relations between travel entities (e.g., users, destinations, itineraries, points of interest).
  • Agentic AI & Generative AI: Familiarity with Agentic AI frameworks, LLM-driven reasoning, or autonomous planning agents to enhance conversational search and automated itinerary generation.
  • Experience working in E-commerce, Travel Tech, or Two-Sided Marketplaces, specifically handling non-linear user journeys and highly constrained inventory (e.g., hotel availability, tour timings).
  • A strong track record of academic or industry contributions, including publications in top-tier AI/IR conferences (e.g., SIGIR, KDD, RecSys, NeurIPS) or open-source ML contributions.
Principal Machine Learning Scientist at Tripadvisor
Position posted a month ago

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Starling Bank on cord

Starling Bank

Full Stack Engineer (ML Ops)

London, UK
FinTech · Banking · Finance
A better bank for everyone
Active
over 6 months ago
Responds to
0% of requests
Responds in
1h 55m
Requests
7 pending

Skills & Experience

Job roles: Full Stack
Experience level: Mid, Senior
Core skills considered: Java, React, Redux, AWS, JavaScript

Logistics

Base salary: £70K - £110K
Employment type: Permanent
Remote working: Hybrid (up to 2 remote days p/w)
Visa sponsorship: Not available

Job Description

Starling is the UK’s first and leading digital bank on a mission to fix banking! Our vision is fast technology, fair service, and honest values. All at the tap of a phone, all the time.

Starling is the UK’s first and leading digital bank on a mission to fix banking! We built a new kind of bank because we knew technology had the power to help people save, spend and manage their money in a new and transformative way.

We’re a fully licensed UK bank with the culture and spirit of a fast-moving, disruptive tech company. We’re a bank, but better: fairer, easier to use and designed to demystify money for everyone. We employ more than 3,000 people across our London, Southampton, Cardiff and Manchester offices.

Our technologists are at the very heart of Starling and enjoy working in a fast-paced environment that is all about building things, creating new stuff, and disruptive technology that keeps us on the cutting edge of fintech. We operate a flat structure to empower you to make decisions regardless of what your primary responsibilities may be, innovation and collaboration will be at the core of everything you do. Help is never far away in our open culture, you will find support in your team and from across the business, we are in this together!

The way to thrive and shine within Starling is to be a self-driven individual and be able to take full ownership of everything around you: From building things, designing, discovering, to sharing knowledge with your colleagues and making sure all processes are efficient and productive to deliver the best possible results for our customers. Our purpose is underpinned by five Starling values: Listen, Keep It Simple, Do The Right Thing, Own It, and Aim For Greatness.

Hybrid Working

We have a Hybrid approach to working here at Starling - our preference is that you're located within a commutable distance of one of our offices so that we're able to interact and collaborate in person. We don't like to mandate how much you visit the office and work from home, that's to be agreed upon between you and your manager.

Our Data Environment

Our Data teams are excited about the value of data within the business, powers our product decisions to improve things for our customers and enhance effective and agile decision making, regardless of what their primary tech stack may be. Hear from the team in our latest blogs or our case studies with Women in Tech.

We are looking for talented data professionals at all levels to join the team. We value people being engaged and caring about customers, caring about the code they write and the contribution they make to Starling. People with a broad ability to apply themselves to a multitude of problems and challenges, who can work across teams do great things here at Starling, to continue changing banking for good.

Requirements

We have built our entire banking platform in house and mostly in Java. We are looking for people who want to work on building the tooling that is used by our engineers on a daily basis.

We are looking for people who are truly full stack, and are as comfortable polishing their javascript front end as they are debugging the innards of their java applications database interactions, or standing up infrastructure with terraform. We are looking for people who can:

  • Design REST apis.
  • Code backend services, ideally using Java, or another other server side compiled language.
  • Develop modern front ends, ideally using React and Redux.
  • Get their code into the cloud and support it there, ideally on AWS.
  • Believe in clean coding, simple solutions, automated testing and continuous deployment.
  • Like to take ownership of a feature from the original idea through to live.
  • Think (like us) that a small number of empowered developers is the right way to deliver software.

Company Benefits

  • 33 days holiday (including flexible bank holidays)
  • An extra day’s holiday for your birthday
  • 16 hours paid volunteering time a year
  • Part-time and/or flexible hours available for most roles
  • Salary sacrifice, company enhanced pension scheme
  • Life insurance at 4x your salary
  • Hybrid/remote working
  • Private Medical Insurance with VitalityHealth including mental health support and cancer care. Partner benefits include discounts with Waitrose, Mr&Mrs Smith and Peloton
  • Generous family-friendly policies
  • Varied social groups set up and run by our employees
  • Perkbox membership giving access to retail discounts, a wellness platform for physical and mental health, and weekly free and boosted perks
  • Access to initiatives like Cycle to Work, Salary Sacrificed Gym partnerships and Electric Vehicle (EV) leasing

Full details are available on our careers site

Interview Process

Interviewing is a two way process and we want you to have the time and opportunity to get to know us, as much as we are getting to know you! Our interviews are conversational and we want to get the best from you, so come with questions and be curious. In general you can expect the below, following a chat with one of our Talent Team:

  • Stage 1 - 30 mins with one of the team
  • Stage 2 - Take home challenge
  • Stage 3 - 90 mins technical interview with two team members
  • Stage 3 - 45 min final with an executive and a member of the people team
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