Staff Machine Learning Engineer – Ads Foundational Representations

🕒 June 19

🌐 United Kingdom, Netherlands – Remote

🇬🇧 United Kingdom – Remote 🇳🇱 Netherlands – Remote

⏰ Full Time

🔴 Lead

🤖 Machine Learning Engineer

👻 Ghost score 31%

What it means: how likely this posting is sitting open without active hiring.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Reddit, Inc.

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2005

💼 Consulting

📣 Marketing

📱 Media

Consulting • Marketing • Media

Reddit, Inc. is a social media platform that acts as a hub for thousands of communities, where users can engage in diverse conversations ranging from breaking news to niche interests. It enables users to post, comment, and vote on content, fostering a vibrant online community. Millions of people globally connect and share their passions on Reddit, creating a dynamic environment for authentic human interaction.

📋 Description

• Set the technical direction of multiple Ads Foundational Representations team pillars • Lead cross-functional machine learning projects end to end, from business gap analysis through engineering execution • Spend approximately 50% of time on technical leadership and mentorship and 50% on hands-on data analysis, engineering, modeling, and automation • Provide technical leadership and mentorship to MLEs through design reviews, best practices, and quality standards • Develop technical strategy for content-based embeddings and relevance for Ads • Develop and iterate embedding models for advertising use cases, including aggregation pipelines, two-tower architectures, and sequence models • Work with local and third-party LLMs/VLMs to extract representations, develop evaluation methods, prompt-tune, and fine-tune large models • Build data processing and inference pipelines • Perform qualitative and quantitative feature evaluation, including benchmarks, recommender-system offline metrics, and online experiments • Ensure ML-system reliability, scalability, and performance through automated tests, monitoring, and model-management best practices • Participate in modeling and coding reviews and provide quality and performance feedback • Collaborate with cross-functional teams to translate business requirements into technical solutions

🎯 Requirements

• 7+ years of hands-on experience with the full lifecycle of designing, training, evaluating, testing, and deploying industry-level models • Demonstrated Staff-level technical leadership: mentoring engineers, driving standards and bar raising, leading complex cross-functional projects from requirements and design to cross-team/functional alignment and execution without direct people-management authority • Excellent communication skills, with the ability to translate complex technical concepts to different audiences, verbally and in writing • Strong track record of working on content rich NLP/CV problems at scale, and using embeddings as a tool to solve them • Established data-driven approach for ML system development • Familiarity with the Ads domain and/or Search/Recommender systems • Experience with mainstream DL frameworks: PyTorch or TensorFlow • Preferred: Experience with Python, PyTorch, Airflow, BigQuery, Ray, Kubernetes, Kafka, and GCP • Preferred: Tech leadership experience mentoring junior engineers and leading complex projects • Preferred: Hands-on experience using, fine-tuning, or building LLMs/VLMs

🏖️ Benefits

• Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support • Family Planning Support • Gender-Affirming Care • Mental Health & Coaching Benefits • Group Personal Pension Scheme with Employer match • Private Medical and Dental Scheme • Income Replacement Programs • Bike to Work scheme • Flexible Vacation & Paid Volunteer Time Off • Generous Paid Parental Leave • Opportunity to opt out of interview recording, transcription and summarization