Senior Machine Learning Engineer

Trustpilot; City of Westminster; Hybrid; GBP 70,000 - 90,000; Full time

Job summary

A leading technology company based in the UK is seeking a highly skilled Senior Machine Learning Engineer to join their MLOps team. The role involves designing and implementing cutting-edge ML infrastructure, collaborating with data science teams, and taking ownership of ML offerings. Ideal candidates will have proven experience with containerisation, Python, and high-volume data processing. This opportunity includes a competitive compensation package and flexible working options.

Benefits

Flexible working options

Competitive compensation package

28 days holiday plus volunteering days

Learning and development opportunities

Pension and life insurance

Health cash plan and online GP

Access to mindfulness app

Paid parental leave

Season ticket loan

Central office location

Regular social events

Qualifications

• Strong experience in a production ML environment.
• Ability to switch between technical implementation and discussions.
• Demonstrated experience in large-scale ML infrastructure.

Responsibilities

• Design and implement ML infrastructure capabilities.
• Work with streaming data at scale.
• Build partnerships with data science teams.
• Take ownership of ML offerings and architecture.
• Productionize and operate ML models and pipelines.

Skills

Containerisation

Python

CI/CD

Streaming data

High-volume data processing

Architecture design

GCP

Kafka streaming

Job description

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.

Responsibilities

• 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.

Qualifications

• 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.

Benefits

• 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.