Senior ML Engineer, Data & Machine Learning

Linktree
London
5 months ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Data Engineer - (Python, SQL, Machine Learning) - Robotics

Senior Machine Learning Engineer - Agentic AI Platform

Senior Machine Learning Engineer

Overview

Senior ML Engineer, Data & Machine Learning role at Linktree. We’re looking for a Senior Machine Learning Engineer who thrives at the intersection of software engineering and applied ML. This role is ideal for engineers who enjoy building real products — not just models — and want to take machine learning systems all the way from data to production. You’ll own the full lifecycle of ML-powered applications: designing data pipelines, building training workflows, integrating models into services, and deploying production-ready features that power delightful user experiences.


You’ll help us test new ideas quickly, by working in lean, build-measure-learn cycles. You’ll develop rapid prototypes, test them on real users, and iterate based on learnings and user feedback.


No hands-on AI/ML experience, no problem! Do you excel at solving end-to-end software problems but don’t have hands-on experience with AI/ML? If you have a computer science, statistics or other relevant STEM background, we’d love for you to learn the ML part on the job. You’ll work in London, with 3 days per week from our office and 2 days per week from home.


Responsibilities

  • You’ll implement, test, and scale a wide variety of ML and AI capabilities, leveraging both established tools and emerging technologies.
  • You’ll own the end-to-end development cycle of ML-powered features, including assessing impact through experimentation.
  • You’ll collaborate with cross-functional teams to integrate ML solutions into our products.
  • You’ll monitor, evaluate, and improve the performance of models and ML-powered features in production.
  • You’ll stay up-to-date with the latest developments in ML and AI to ensure we’re always operating at the cutting-edge.

Qualifications

  • Strong software engineering background with experience in building and maintaining production systems.
  • Hands-on experience with ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn) and MLOps tools (e.g., Airflow, MLflow, Vertex AI, or similar).
  • Solid understanding of data engineering practices, including ETL, batch/streaming pipelines, and data quality monitoring.
  • Familiarity with cloud infrastructure (AWS, GCP, Azure) and containerization.
  • Experience with shortening build-measure-learn cycles via prototyping and experimentation to iterate quickly and build software users love.

Compensation

The base salary offered for this role is targeted at $80,000-$110,000 GBP for roles based in United Kingdom. Final offers depend on multiple factors including location, experience, expertise, and role scope, and may vary from the range listed.


Location & How We Work

London, England, United Kingdom — hybrid: 3 days per week in the office, 2 days remote. We’re a global, diverse team with offices in London, Los Angeles, Melbourne, and San Francisco. We offer autonomy in how you structure your days and weeks and support async collaboration where possible.


Benefits

  • An annual wellbeing allowance to use on things like fitness memberships, development courses, childcare, travel, charitable donations, etc.
  • Employer contribution towards retirement.
  • Generous time off for vacation, holidays, parental leave, volunteer time, and other categories.
  • Employee stock option program to share in the company’s success.

Work inclusivity

Linktree is an equal opportunity workplace committed to inclusion. We welcome all people regardless of sex, gender identity, race, ethnicity, disability, pregnancy, age, or other lived experience. If you require accommodations to participate fully, please contact .


#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.

How Many Machine Learning Tools Do You Need to Know to Get a Machine Learning Job?

Machine learning is one of the most exciting and rapidly growing areas of tech. But for job seekers it can also feel like a maze of tools, frameworks and platforms. One job advert wants TensorFlow and Keras. Another mentions PyTorch, scikit-learn and Spark. A third lists Mlflow, Docker, Kubernetes and more. With so many names out there, it’s easy to fall into the trap of thinking you must learn everything just to be competitive. Here’s the honest truth most machine learning hiring managers won’t say out loud: 👉 They don’t hire you because you know every tool. They hire you because you can solve real problems with the tools you know. Tools are important — no doubt — but context, judgement and outcomes matter far more. So how many machine learning tools do you actually need to know to get a job? For most job seekers, the real number is far smaller than you think — and more logically grouped. This guide breaks down exactly what employers expect, which tools are core, which are role-specific, and how to structure your learning for real career results.

What Hiring Managers Look for First in Machine Learning Job Applications (UK Guide)

Whether you’re applying for machine learning engineer, applied scientist, research scientist, ML Ops or data scientist roles, hiring managers scan applications quickly — often making decisions before they’ve read beyond the top third of your CV. In the competitive UK market, it’s not enough to list skills. You must send clear signals of relevance, delivery, impact, reasoning and readiness for production — and do it within the first few lines of your CV or portfolio. This guide walks you through exactly what hiring managers look for first in machine learning applications, how they evaluate CVs and portfolios, and what you can do to improve your chances of getting shortlisted at every stage — from your CV and LinkedIn profile to your cover letter and project portfolio.

MLOps Jobs in the UK: The Complete Career Guide for Machine Learning Professionals

Machine learning has moved from experimentation to production at scale. As a result, MLOps jobs have become some of the most in-demand and best-paid roles in the UK tech market. For job seekers with experience in machine learning, data science, software engineering or cloud infrastructure, MLOps represents a powerful career pivot or progression. This guide is designed to help you understand what MLOps roles involve, which skills employers are hiring for, how to transition into MLOps, salary expectations in the UK, and how to land your next role using specialist platforms like MachineLearningJobs.co.uk.