Engineer the Quantum RevolutionYour expertise can help us shape the future of quantum computing at Oxford Ionics.

View Open Roles

MLOps Engineer II (Remote or Hybrid)

TripAdvisor LLC
London
2 weeks ago
Applications closed

Related Jobs

View all jobs

Mid-Level Machine Learning Engineer - Data Engineer II - Chase

Senior/ Principal Data Engineering Consultant- London

Senior Machine Learning Scientist

MLOps Engineer

Tech Lead – AI/ML, GenAI, Data Engineering

Senior MLOps Engineer

We believe that we are better together, and at Tripadvisor we welcome you for who you are. Our workplace is for everyone, as is our people powered platform. At Tripadvisor, we want you to bring your unique perspective and experiences, so we can collectively revolutionize travel and together find the good out there.

We have a fun and friendly environment where the key objective is getting things done. Our engineers are part of the full process from design, to code, to test, to deployment and back again for further iteration.

Our team is building the Machine Learning Platform for all data scientists across Tripadvisor. Our mission is to make data scientists more productive and to enable broader and deeper utilization of machine learning techniques to help improve the business performance.

We use a variety of 3rd party packages, including MLFlow, Seldon for ML model tracking and deployment, Kubernetes for hosting models, Argo and Git for CI/CD automation, Spark for big data processing. This is a rapidly changing field and we are deeply involved in open source community to help shape the technology evolution and are constantly looking for components to adopt in order to enhance our platform.

What you’ll do:

  • Develop across our evolving technology stack - we’re using Python, Java, Kubernetes, Apache Spark, Postgres, ArgoCD, Argo Workflow, Seldon, MLFlow and more. We are migrating into AWS cloud and adopting many services that are available in that environment.
  • You will have the opportunity to learn many cutting edge technologies around Machine Learning Platform. You will push the boundaries, to test, develop and implement new ideas, technology and opportunities, and be well rewarded and recognized for doing so.
  • Take responsibility for all aspects of software engineering, from design to implementation, QA and maintenance.
  • Touch code at every level – from the UI, backend microservices, database, big data processing, operations, to CD/CI automation.
  • Collaborate closely with data science teams to define feature specifications and develop high quality deliverables for our customers.
  • Take ownership for the quality of the code.

Skills and Experience:

  • At least 5 years’ experience of commercial software development.
  • Willingness and ability to take on new technologies.
  • Ability to break down complex problems into simple solutions.
  • Strong analytical skills and desire to write clean, correct and efficient code.
  • Sense of ownership, urgency and pride in your work.
  • Experience with Python, Java, Docker, Kubernetes, Argo, Spark and AWS cloud services a plus.
  • Exposure to Machine Learning practices a plus.

We strive to create an accessible and inclusive experience for all candidates. If you need a reasonable accommodation during the application or the recruiting process, please make sure to reach out to your individual recruiter or our team at .

Apply for this job
#J-18808-Ljbffr

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

The Future of Machine Learning Jobs: Careers That Don’t Exist Yet

Machine learning (ML) has quickly become one of the most transformative forces in modern technology. What began as a subset of artificial intelligence—focused on algorithms that learn from data—has grown into a foundational capability across industries. From voice assistants and recommendation systems to fraud detection and predictive healthcare, machine learning underpins countless innovations shaping daily life. In the UK, demand for ML professionals has surged. Financial services, healthcare providers, retailers, and tech start-ups are investing heavily in ML talent. Roles like Machine Learning Engineer, Data Scientist, and AI Researcher are among the most sought-after and best-paid in the tech sector. Yet we are still only at the start. Advances in generative AI, quantum computing, edge intelligence, and ethical governance are reshaping the field. Many of the most critical machine learning jobs of the next 10–20 years don’t exist yet. This article explores why new careers will emerge, the kinds of roles likely to appear, how today’s jobs will evolve, why the UK is well positioned, and how professionals can prepare.

Seasonal Hiring Peaks for Machine Learning Jobs: The Best Months to Apply & Why

The UK's machine learning sector has evolved into one of Europe's most intellectually stimulating and financially rewarding technology markets, with roles spanning from junior ML engineers to principal machine learning scientists and heads of artificial intelligence research. With machine learning positions commanding salaries from £32,000 for graduate ML engineers to £160,000+ for senior principal scientists, understanding when organisations actively recruit can dramatically accelerate your career progression in this pioneering and rapidly evolving field. Unlike traditional software engineering roles, machine learning hiring follows distinct patterns influenced by AI research cycles, model development timelines, and algorithmic innovation schedules. The sector's unique combination of mathematical rigour, computational complexity, and real-world application requirements creates predictable hiring windows that strategic professionals can leverage to advance their careers in developing tomorrow's intelligent systems. This comprehensive guide explores the optimal timing for machine learning job applications in the UK, examining how enterprise AI strategies, academic research cycles, and deep learning initiatives influence recruitment patterns, and why strategic timing can determine whether you join a groundbreaking AI research team or miss the opportunity to develop the next generation of machine learning algorithms.

Pre-Employment Checks for Machine Learning Jobs: DBS, References & Right-to-Work and more Explained

Pre-employment screening in machine learning reflects the discipline's unique position at the intersection of artificial intelligence research, algorithmic decision-making, and transformative business automation. Machine learning professionals often have privileged access to proprietary datasets, cutting-edge algorithms, and strategic AI systems that form the foundation of organizational competitive advantage and automated decision-making capabilities. The machine learning industry operates within complex regulatory frameworks spanning AI governance directives, algorithmic accountability requirements, and emerging ML ethics regulations. Machine learning specialists must demonstrate not only technical competence in model development and deployment but also deep understanding of algorithmic fairness, AI safety principles, and the societal implications of automated decision-making at scale. Modern machine learning roles frequently involve developing systems that impact hiring decisions, financial services, healthcare diagnostics, and autonomous operations across multiple regulatory jurisdictions and ethical frameworks simultaneously. The combination of algorithmic influence, predictive capabilities, and automated decision-making authority makes thorough candidate verification essential for maintaining compliance, fairness, and public trust in AI-powered systems.