About this role
Engineers who enjoy building platforms that empower data science stakeholders and want to shape travel technology will thrive in this environment. Tripadvisor Experiences Engineering operates the leading marketplace for travel experiences, connecting a global audience with hundreds of thousands of tours and activities through advanced machine learning and data science.
This intermediate role sits within the Internal Systems pillar, focusing on the evolution of scalable infrastructure to support pre-computed, batch, and real-time models. The incoming engineer will provide necessary tooling and support for seamless machine learning execution while collaborating closely with cross-functional partners in a hybrid setup based in London.
What you will do
- Empower data science and machine learning stakeholders by providing the tools and infrastructure necessary for seamless execution of AI processes.
- Support technology stack evolution by developing across the existing AWS cloud environment and adopting the latest available solutions.
- Build and maintain robust infrastructure supporting pre-computed, batch, and real-time model needs to reduce time-to-market.
- Take full responsibility for software engineering aspects ranging from design to implementation, quality assurance, and maintenance.
- Monitor and support machine learning pipelines for accuracy, drift, enhancements, service level agreements, and billing volumes.
- Collaborate with cross-functional stakeholders to define and document requirements for impactful machine learning and AI products.
What you need
- Bring at least two years of MLOps experience building modern machine learning infrastructure that caters to all model lifecycle stages.
- Demonstrate hands-on experience with AWS and/or GCP for scalable and reliable MLOps solutions.
- Possess a good grasp of infrastructure-as-code tools such as Terraform or CloudFormation.
- Show the ability to develop across a diverse technology stack and maintain a willingness to adopt new technologies.
- Demonstrate experience participating in cross-functional teams within fast-paced environments alongside strong CI/CD knowledge.
- Exhibit high-quality verbal and written communication skills with an independent working style and strong sense of ownership.
Nice to have
- Previous exposure to Seldon, KServe, RayServe, Kubernetes, MLFlow, Sagemaker, Kubeflow, Anyscale, Valohai, ArgoCD, Docker, Python, Java, Ray, Spark, Pandas, Argo Workflow, Postgres, Snowflake, and BigQuery
- Knowledge managing complementary databases like vector and/or graph databases
- Hands-on experience in model optimization for high throughput and low latency applications with a focus on cost
- Experience with LLMOps leveraging open source models
Benefits
- Competitive compensation packages including base salary, annual bonus, and equity
- Flexible schedule and work-your-way hybrid approach supporting work-life balance
- Donation matching for qualifying charitable contributions annually
- Tuition assistance for qualified learning programs
- Lifestyle benefit for travel, wellness, or personal use
- Travel perks including discounts and employee assistance programs
Skills and tech stack
Questions candidates ask
What is the remote work and office policy for this role?
This is a hybrid role based in London, opened for all the candidates who are already based in London or max 1.5 hours away. It features a relaxed hybrid schedule requiring attendance approximately two times per month.
What compensation and perks are included?
The position offers competitive compensation packages including base salary, annual bonus, and equity. Additional perks include lifestyle benefits, travel discounts, tuition assistance, and annual donation matching.
What tools and technologies will I work with?
The technology stack runs in the AWS cloud and includes infrastructure-as-code tools like Terraform or CloudFormation. Exposure to technologies such as Kubernetes, MLFlow, Docker, Python, Snowflake, and BigQuery is highly desirable.
What kind of team will I be joining?
You will join the Tripadvisor Experiences Engineering team within the Internal Systems pillar, which focuses on harnessing AI, machine learning, and data science to drive innovation and growth.