23 days ago
Remote, United Kingdom or Remote, NetherlandsStaff+
Responsibilities
- Provide technical leadership and mentorship to machine learning engineers, including driving designs, reviews, engineering standards, and quality practices.
- Develop technical strategy for content-based embeddings and advertising relevance in collaboration with team and organizational leadership.
- 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 and VLMs to extract representations, develop evaluation methods, prompt-tune and fine-tune large models, and build embeddings.
- Build data-processing and inference pipelines for machine learning models.
- Evaluate features through qualitative and quantitative analysis, internal benchmarks, recommender-system offline metrics, and online experiments.
- Ensure ML-system reliability, scalability, and performance through automated tests, monitoring, and model-management practices.
- Review modeling and coding work and provide feedback on quality and performance.
- Collaborate with cross-functional teams to understand business requirements and translate them into technical solutions.
Requirements
- 7+ years of hands-on experience designing, training, evaluating, testing, and deploying industry-level models across the full lifecycle.
- Demonstrated staff-level technical leadership, including mentoring engineers, setting standards, raising quality, and leading complex cross-functional projects without direct people-management authority.
- Excellent verbal and written communication skills, including the ability to explain complex technical concepts to different audiences.
- Strong experience solving content-rich NLP and computer-vision problems at scale and using embeddings to address them.
- A data-driven approach to ML-system development and strong enthusiasm for working with data and investigating metric results.
- Familiarity with the advertising domain and/or search or recommender systems.
- Experience with mainstream deep-learning frameworks such as PyTorch or TensorFlow.
- Preferred experience with Python, PyTorch, Airflow, BigQuery, Ray, Kubernetes, Kafka, and GCP.
- Preferred experience mentoring junior engineers and leading complex projects.
- Preferred hands-on experience using, fine-tuning, or building LLMs.
Benefits
- Flexible remote work from anywhere in the UK or the Netherlands.
- Global benefit programs covering workspace, professional development, and caregiving support.
- Family planning support, gender-affirming care, and mental health and coaching benefits.
- Group personal pension scheme with employer match, private medical and dental coverage, and income replacement programs.
- Bike to Work scheme, flexible vacation, paid volunteer time off, and generous paid parental leave.
Tech Stack
Categories
About Reddit
Reddit builds a social news and discussion platform organized into user-created forums (“subreddits”) for consumers, creators, and communities. It monetizes primarily through advertising tools for brands and self-serve advertisers, plus a Premium subscription; developers can access data via its API. Founded in 2005 and headquartered in San Francisco, Reddit became a public company on the NYSE in 2024 and hosts over 100,000 active communities.