ML Ops Engineer II (Experiences)
- Compensation
- Not disclosed
- Location
- UK
- Work setup
- Hybrid
- Seniority
- Middle
- Employment
- Not specified
- Experience
- 2+ years
- Category
- Devops
- Posted
Skills
Must have
- 2+ years of MLOps experience, participating in building modern ML infrastructure catering to all stages of a model lifecycle.
- Hands-on experience with AWS and/or GCP, demonstrating proficiency in leveraging cloud services for scalable and reliable MLOps solutions.
- Have a good grasp of IaC (Infrastructure-as-code) tools like Terraform or CloudFormation.
- Previous exposure to additional technologies like Seldon, KServe, RayServe, Kubernetes, MLFlow, Sagemaker, Kubeflow, Anyscale, Valohai, ArgoCD, Docker, Python, Java, Ray, Spark, Pandas, Argo Workflow,
- Good to have: previous knowledge managing complementary DBs like vector and/or graph DBs
- Good to have: Hands-on experience in model optimization with experience in handling high throughput and low latency applications with an eye on cost.
- Good to have: Experience with LLMOps leveraging open source models
- Ability to develop across a diverse technology stack and willingness and ability to take on new technologies.
- Demonstrated experience participating in cross-functional teams in fast-paced environments.
- Experience with CI/CD processes and platforms.
- Ability to effectively operate both independently and as part of a team.
- Sense of ownership, urgency and pride in your work.
- High-quality verbal and written communication skills.
Full description
About Tripadvisor
The Tripadvisor Group connects people to experiences worth sharing, and aims to be the world’s most trusted source for travel and experiences. We leverage our brands, technology, and capabilities to connect our global audience with partners through rich content, travel guidance, and two-sided marketplaces for experiences, accommodations, restaurants, and other travel categories. The subsidiaries of Tripadvisor, Inc. (Nasdaq: TRIP), include a portfolio of travel brands and businesses, including Tripadvisor, Viator, and TheFork.
Tripadvisor Experiences Engineering is the team that builds and supports the world's leading marketplace for travel experiences. We believe that making memories is what travel is all about. And with 400,000+ travel experiences to explore—everything from simple tours to extreme adventures (and everything in between) —making memories that will last a lifetime has never been easier.
Our Internal Systems pillar is at the forefront of transforming how we harness AI, Machine Learning and Data Science to drive innovation and growth. To address the increasing traffic and deliver a cutting-edge platform, the team is in search of a MLOps Engineer to join and support Tripadvisor’s growth.
We are looking for an intermediate level MLOps Engineer to join the team. If you're passionate about creating ML/AI Platforms that empower teams to enhance customer experiences, we’d love to have you on board!
This is a hybrid role based in London, opened for all the candidates who are already based in London or max 1,5h away. (relaxed hybrid, 2x per month)
What you'll do:
- Empowering Data Science and ML stakeholders, by providing the tools and support the infrastructure necessary for seamless execution of machine learning and AI processes.
- Support tech stack evolution by developing across our existing technology stack running in AWS cloud, leveraging and adopting the latest solutions available in that environment.
- Build and maintain a robust and scalable infrastructure to support pre-computed, batch and real-time model needs, ensuring smooth deployment and reducing time-to-market of machine learning models.
- Take responsibility for all aspects of software engineering, from design to implementation, QA, and maintenance.
- Monitor and support ML pipelines for accuracy, drifts, enhancements, changes, SLA, and billing volumes to ensure all models are processed accurately and when needed.
- Foster a culture of innovation by generating and promoting new ideas within the MLOps domain.
- Work with cross-functional stakeholders in defining and documenting requirements for building high-quality and impactful ML/AI products.