Staff Machine Learning Engineer (Ads Foundational Representations)

Location: Remote from the UK or the Netherlands

Company

Reddit operates a large community platform with more than 100,000 active communities and approximately 130 million daily active unique visitors.

What you will do

• Set the technical direction for multiple Ads Foundational Representations pillars and provide technical leadership and mentorship to machine learning engineers.
• Develop and iterate on embedding models for advertising use cases, including aggregation pipelines, two-tower architectures, and sequence models.
• Use local and third-party LLMs, VLMs, and foundational models to build representations and fine-tune models for high-quality embeddings.
• Build data processing, training, and inference pipelines for machine learning models.
• Evaluate features through internal benchmarks, recommender-system offline metrics, and online experiments.
• Improve ML system reliability, scalability, and performance through automated testing, monitoring, model management, and engineering reviews.

Requirements

• 7+ years of hands-on experience designing, training, evaluating, testing, and deploying industry-level models across their full lifecycle.
• Staff-level technical leadership experience, including mentoring engineers, setting standards, and leading complex cross-functional projects without direct people-management authority.
• Strong experience with content-rich NLP or computer vision problems at scale and with embeddings.
• Experience with data-driven ML system development and quantitative and qualitative model evaluation.
• Familiarity with advertising, search, or recommender systems.
• Experience with PyTorch or TensorFlow and strong written and verbal communication skills.

Nice to have

• Experience with Python, Airflow, BigQuery, Ray, Kubernetes, Kafka, and GCP.
• Hands-on experience using, fine-tuning, or building LLMs.
• Experience mentoring junior engineers and leading complex projects.

Culture & Benefits

• Flexible remote-first work options for eligible locations.
• Workspace, professional development, and caregiving support.
• Family planning support, gender-affirming care, and mental health and coaching benefits.
• Private pension plan with employer matching and an employer-sponsored group medical plan.
• Flexible vacation, paid volunteer time off, paid parental leave, and income replacement programs.

Hiring process

• Some interviews may be recorded, transcribed, and summarized by AI; opting out is available before scheduled interviews.