Senior Machine Learning Engineer at Trustpilot Ltd

London, England, United Kingdom -

Full Time

Start Date

Immediate

Expiry Date

15 Feb, 26

Salary

0.0

Posted On

17 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Containerisation, Python, CI/CD, Machine Learning, Streaming Data, High-Volume Data Processing, Architecture Design, GCP, Kafka, Scientific Thinking, Critical Thinking, Mentoring, MLOps Principles, Agile Methodologies, Technical Leadership, Collaboration

Industry

technology;Information and Internet

Description

At Trustpilot, we're on an incredible journey. We're a profitable, high-growth FTSE-250 company with a big vision: to become the universal symbol of trust. We run the world's largest independent consumer review platform, and while we've come a long way, there's still so much exciting work to do. Come join us at the heart of trust! We are looking for a highly skilled Senior Machine Learning Engineer to join our MLOps team at Trustpilot. You will work closely with data science teams and engineering stakeholders to design, implement, and take ownership of cutting-edge ML infrastructure solutions that are core to Trustpilot's central strategy. As a Senior ML Engineer, you will be a key driver in defining our technical roadmap, enabling data scientists to deliver value at massive scale and you'll be working with the latest technologies including LLMs, MCP servers, and streaming-based models while acting as a bridge between data science teams and classical engineering. A typical week for you will include working in a semi-embedded model, collaborating closely with data science teams while maintaining your agile rituals within the MLOps team. You'll have the freedom to define how you solve technical problems while meeting clear expectations set by your engineering manager. You'll participate in cross-functional delivery of projects and help educate other teams on ML best practices. You'll also have regular 1-on-1s with your manager, where you'll work on your personal growth and development through clear goals, actionable feedback, and learning opportunities. What you'll be doing: Design and implement machine learning infrastructure capabilities using cutting-edge technology like LLMs and MCP servers. Work with streaming data and high-volume data that supports machine learning infrastructure. Build solid contributing partnerships with data science teams to deeply understand their use cases and deliver value. Take full ownership of ML offerings, including architecture decisions and defining interfaces with data scientists. Productionize and operate ML models and pipelines at scale with a focus on reliability and efficiency. Act as a bridge and technical leader between data science teams and classical engineering. Identify opportunities and implement best practices to improve our existing systems continuously. Help mentor and educate colleagues across different teams on ML best practices and MLOps principles. Who you are: Strong, proven experience with containerisation, Python, and CI/CD in a production ML environment. Expert experience working with streaming data and high-volume data processing at scale. Ability to quickly switch between complex technical implementation and value-focused discussions with data scientists (a consulting mindset). Demonstrated experience in architecture design and taking ownership of large-scale ML infrastructure. Experience with GCP and Kafka streaming is a strong plus. Scientific and critical thinking skills, combined with the ability to present your ideas clearly and compellingly. A friendly and helpful personality, open to give and receive feedback in a constructive way. Motivation to push yourself and the people around you to constantly improve and define the technical roadmap. This is a hybrid role with flexibility on location, requiring some in-office presence (at least one day per week) to build relationships with data science teams. What’s in it for you: A range of flexible working options to dedicate time to what matters to you Competitive compensation package, with bonus and RSU 28 days holiday plus two (paid) volunteering days a year to spend your time giving back to the causes that matter to you and your community Rich learning and development opportunities supported through the Trustpilot Academy, LinkedIn Learning and Blinkist Pension and life insurance Health cash plan, online GP, 24/7 Employee Assistance Plan Full access to Headspace, a popular mindfulness app to promote positive mental health Paid parental leave Season ticket loan and a cycle to work scheme Central office location complete with all the snacks and refreshments you can ask for Regular opportunities to connect and get to know your fellow Trusties, including company-wide celebrations and events, ERG activities and team socials. There is also breakfast and lunch in the office on Tuesdays and Wednesdays along with extra treats throughout the month Access to over 4,000 deals and discounts on things like travel, electronics, fashion, fitness, cinema discounts and more. Still not sure? We are Open to All, which means we want everyone to feel like they can see themselves at Trustpilot. We're keen to hear about your experiences as well as how you can help to create a fantastic culture for our amazing Trusties. So, don't worry if you're looking at this job description and feel like you don't meet all the requirements, we'd still really like to hear from you! About us Trustpilot began in 2007 with a simple yet powerful idea that is more relevant today than ever — to be the universal symbol of trust, bringing consumers and businesses together through reviews. Trustpilot is open, independent, and impartial — we help consumers make the right choices and businesses to build trust, grow and improve. Today, we have more than 300 million reviews and 64 million monthly active users on average across the globe, with 140 billion annual Trustbox impressions, and the numbers keep growing. We have more than 1,000 employees and we’re headquartered in Copenhagen, with operations in Amsterdam, Denver, Edinburgh, Hamburg, London, Melbourne, Milan and New York. We’re driven by connection. It’s at the heart of what we do. Our culture keeps things fresh –– it’s built on the relationships we create. We talk, we laugh, we collaborate and we respect each other. We work across borders and cultures to be the universal symbol of trust in an ever-changing world. With vibrant office locations worldwide and over 50 nationalities, we’re proud to be an equal opportunity workplace with diverse perspectives and ideas. Our purpose to help people and businesses help each other is a tall order, but we keep it real. We’re a great bunch of humans, doing awesome stuff, without fuss or pretense. A successful Trustpilot future is driven by you –– we give you the autonomy to shape a career you can be proud of. If you’re ready to grow, let’s go. Join us at the heart of trust. Trustpilot is committed to creating an inclusive environment where people from all backgrounds can thrive and where different viewpoints and experiences are valued and respected. Trustpilot will consider all applications for employment without regard to race, ethnicity, national origin, religious beliefs, gender identity or expression, sexual orientation, neurodiversity, disability, age, parental or veteran status. Together, we are the heart of trust. Trustpilot is a global company and our data practices are designed to ensure that your personally identifiable information is appropriately protected. Please note that your personal information will be transferred, accessed, and stored globally as necessary for the uses and disclosures stated in our Privacy Policy. If you have a disability and would like to discuss any adjustments you might need either in submitting your application, or to the recruitment process more generally, please let us know by contacting our People Team at HR@trustpilot.com, quoting the role you wish to apply for.

Responsibilities

Design and implement machine learning infrastructure capabilities using cutting-edge technology. Collaborate closely with data science teams to understand their use cases and deliver value.