Staff Machine Learning Engineer – Ads Foundational Representations

🕒 il y a 4 mois

🌐 Royaume-Uni, Pays-Bas – Distant

🇬🇧 Royaume-Uni – Télétravail 🇳🇱 Pays-Bas – Télétravail

⏰ Temps Plein

🔴 Expert

🤖 Ingénieur Machine Learning

👻 Score fantôme 52%

Ce que ça veut dire : la probabilité que personne ne recrute vraiment pour cette offre.Comment le lire : 60 % ou plus, on pense que c'est une offre fantôme. Un score plus bas est moins inquiétant.Comment on la calcule : ancienneté, republications, postes ouverts vs taille de l'équipe, rapidité de clôture, et si le salaire est indiqué.À noter : une estimation à partir de données publiques, pas un jugement sur l'entreprise. De vraies offres peuvent avoir un score élevé, alors prenez-le comme un indice, pas comme un fait.

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Reddit, Inc.

Site WebLinkedInTous les Emplois

501 - 1000 employés

Fondée en 2005

💼 Conseil

📣 Marketing

📱 Médias

Consulting • Marketing • Media

Reddit, Inc. est une plateforme de médias sociaux qui fait office de hub pour des milliers de communautés, où les utilisateurs peuvent participer à des conversations variées, allant des dernières actualités aux centres d’intérêt les plus pointus. Elle permet aux utilisateurs de publier, de commenter et de voter sur des contenus, favorisant une communauté en ligne dynamique. Des millions de personnes à travers le monde se connectent et partagent leurs passions sur Reddit, créant un environnement propice à des interactions humaines authentiques.

Description

• Provide technical leadership and mentorship to MLEs, driving designs and reviews, establishing analysis, modeling, and engineering best practices, and maintaining quality standards • Work with team and organizational leadership to develop technical strategy for content-based embeddings and Ads relevance • Develop or iterate on 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 methodologies, prompt-tune, and fine-tune large models • Build data processing and inference pipelines • Perform qualitative and quantitative feature evaluation and end-to-end experimentation, from internal benchmarks through 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 • Set technical direction across multiple team-owned pillars and lead cross-functional ML projects from business-gap analysis through engineering execution • Split time between technical leadership and mentorship and hands-on data analysis, engineering, modeling, and automation

🎯 Exigences

• 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 to solve them • Established data-driven approach for ML system development and readiness to investigate metric numbers • Familiarity with the Ads domain and/or Search/Recommender systems • Experience with mainstream deep learning frameworks: PyTorch or TensorFlow • Preferred: experience with Python, PyTorch, Airflow, BigQuery, Ray, Kubernetes, Kafka, and GCP • Preferred: hands-on experience using, fine-tuning, or building LLMs

🏖️ Avantages

• 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

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