Senior Machine Learning Engineer, Tumblr

myGwork
UK
1 year ago
Applications closed

Related Jobs

View all jobs

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

Senior Machine Learning Engineer

This job is with Automattic, an inclusive employer and a member of myGwork – the largest global platform for the LGBTQ business community. Please do not contact the recruiter directly. Tumblr launched in 2007 with the belief that people need a place to say what they want, be who they want, and connect over their interests. We continue to build Tumblr as a platform for free expression, individuality, and human connection. We are looking for an experienced candidate to join our Feeds Experience team, which builds Tumblr's backend systems-powering core content feeds, search, personalization/discovery experiences, user-interest profiling, content understanding and notifications. Your goal will be to design, develop and maintain large-scale data pipelines and backend services, to connect users with the content they love. The team plays a critical role in driving daily active users by improving engagement and retention on Tumblr.We build on top of open source big-data frameworks, such as Apache Spark (batch processing) and Apache Flink (real-time processing), orchestrated by Kubernetes, Apache Airflow, and with a PHP backend layer.Responsibilities: Collaborate with the team to enhance engagement on feeds, notifications, content discovery and relevance of search results. This will involve developing algorithms, data-pipelines and backend-services to match millions of users with the most relevant and engaging content, detecting trends, improving search retrieval and relevance, and striking a balance between driving engagement to established and new content creators. Research and develop new features to improve user engagement and the reactivation of lapsed users. Define success metrics, launch A/B tests, perform analysis to validate hypotheses, and build tools to enable continuous experimentation.With stakeholders from Engineering, Product, and User Research, contribute to the team's strategy and roadmap. This includes identifying short- and long-term opportunities for business impact on Feeds, Search, and Notifications; discussing alternatives; driving architectural decisions and implementation; and,finally, quantifying the impact of implemented solutions and distilling learnings.Requirements: Good understanding of statistics, machine learning, and mining of massive datasets.3 years of professional experience developing large-scale data-pipelines and machine learning approaches for content retrieval, ranking, relevance, and personalization. 5 years of professional experience in software engineering, with expertise in at least one among the following programming languages: Python, Scala, Java. You will encounter all of them in this role, as well as PHP; the idea of using them on a regular basis should not be a blocker for you.Have hands-on experience with data processing frameworks like Apache Spark and Apache Flink at scale. You have excellent written English and can effectively communicate with stakeholders and colleagues from a cross functional organization. Communication is our oxygen and the basis of everything we do.You are goal driven, humble, and have equal willingness to learn and teach. Excitement to join a globally distributed team. Familiarity with remote and async work is welcome.What will make you stand out:MS/PhD in Computer Science, ML, or related fields.Experience in large-scale notifications systems for driving user growth and engagement loops.Deep expertise in search ranking and relevance at scale, in particular with Elasticsearch.Experience in embedding-based recommendation and retrieval.Experience in real-time stream processing frameworks.Salary range: $100,000-$200,000 USD - Please note that salary ranges are global, regardless of location, and we pay in local currency.This isn't your typical work-from-home job-we are a fully-remote company with an open vacation policy. Read more about our compensation philosophy. To see a full list of benefits by country, consult our Benefits Page. And check out these links to learn more about How We Hire and What We Expect from Ourselves. About Automattic We are the people behind WordPress.com, WooCommerce, Tumblr, Simplenote, Jetpack, Longreads, Day One, PocketCasts, and more. We believe in making the web a better place.We're a distributed company with more than 1900 Automatticians in 96 countries speaking 120 different languages. And, even more than growth and profitability (although we're plenty profitable), above all, we're driven by a mission: We democratize publishing and commerce so anyone with a story can tell it, and anyone with a product can sell it, regardless of income, gender, politics, language, or country.We believe in Open Source, and the vast majority of our work is available under the GPL.Diversity, Equity, & Inclusion at Automattic We're improving diversity in the tech industry. At Automattic, we want people to love their work and show respect and empathy to all. We welcome differences and strive to increase participation from traditionally underrepresented groups. Our DEI committee involves Automatticians across the company and drives grassroots change. For example, this group has helped facilitate private online spaces for affiliated Automatticians to gather and helps run a monthly DEI People Lab series for further learning. DEI is a priority at Automattic, though our dedication influences far more than just Automatticians: We make our products freely available and translate our products into and offer customer support in numerous languages. We require unconscious bias training for our hiring teams and ensure our products are accessible across different bandwidths and devices. Automattic is a Most Loved Company and Disability Confident Committed. (Here's what that might mean for you.) Learn more about our dedication to diversity, equity, and inclusion and our Employee Resource Groups.

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 AI Tools Do You Need to Know to Get an AI Job?

If you are job hunting in AI right now it can feel like you are drowning in tools. Every week there is a new framework, a new “must-learn” platform or a new productivity app that everyone on LinkedIn seems to be using. The result is predictable: job seekers panic-learn a long list of tools without actually getting better at delivering outcomes. Here is the truth most hiring managers will quietly agree with. They do not hire you because you know 27 tools. They hire you because you can solve a problem, communicate trade-offs, ship something reliable and improve it with feedback. Tools matter, but only in service of outcomes. So how many AI tools do you actually need to know? For most AI job seekers: fewer than you think. You need a tight core toolkit plus a role-specific layer. Everything else is optional. This guide breaks it down clearly, gives you a simple framework to choose what to learn and shows you how to present your toolset on your CV, portfolio and interviews.

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

Hiring managers do not start by reading your CV line-by-line. They scan for signals. In AI roles especially, they are looking for proof that you can ship, learn fast, communicate clearly & work safely with data and systems. The best applications make those signals obvious in the first 10–20 seconds. This guide breaks down what hiring managers typically look for first in AI applications in the UK market, how to present it on your CV, LinkedIn & portfolio, and the most common reasons strong candidates get overlooked. Use it as a checklist to tighten your application before you click apply.

The Skills Gap in AI Jobs: What Universities Aren’t Teaching

Artificial intelligence is no longer a future concept. It is already reshaping how businesses operate, how decisions are made, and how entire industries compete. From finance and healthcare to retail, manufacturing, defence, and climate science, AI is embedded in critical systems across the UK economy. Yet despite unprecedented demand for AI talent, employers continue to report severe recruitment challenges. Vacancies remain open for months. Salaries rise year on year. Candidates with impressive academic credentials often fail technical interviews. At the heart of this disconnect lies a growing and uncomfortable truth: Universities are not fully preparing graduates for real-world AI jobs. This article explores the AI skills gap in depth—what is missing from many university programmes, why the gap persists, what employers actually want, and how jobseekers can bridge the divide to build a successful career in artificial intelligence.