Senior Machine Learning Engineer, Ads Foundational Representations

Details

• Multimodal & Content Embeddings - Make sense of organic (posts, comments, subreddits) and promoted (ads, shopping products, their landing pages) text and media content by embedding them into a shared space.
• Contextual and Behavioral Relevance - Working with Product & Data Science, establishing definitions of what ads are relevant to users and the content we show them next to, building metrics and fine-tuning embeddings to better reflect relevance.
• Knowledge Graph Embeddings - Building representations for the Knowledge graph entities, e.g., intellectual properties/brands, to be used for high-precision targeting & business insights.
• User Intent Modeling - Leveraging various techniques to introduce user representations based on the content they interact with: batch & real-time sequence modeling, LLM summarization, etc.
• LLM-based Representations - Leveraging LLMs, VLMs, and foundational models to build complex representations of Reddit entities that improve ranking outcomes
• Developing new or iterating on existing embedding models for advertising use cases, ranging from aggregation pipelines to two-tower architectures and sequence models.
• Working with local and 3rd-party LLMs/VLMs: extract representations, develop evaluation methodologies, prompt tune and fine-tune large models to build state-of-the-art embeddings.
• Building data processing and inference pipelines for the models we develop.
• Qualitative and quantitative evaluation of the various features we develop, end-to-end experimentation from internal benchmarks to downstream recommender system offline metrics to online experiments.
• Ensuring the reliability, scalability, and performance of the ML systems by writing automated tests, monitoring performance, and implementing best practices for model management.
• Participating in modeling and coding reviews: You will review work by other team members and provide feedback to ensure that it meets the team's standards for quality and performance.
• Collaborating with cross-functional teams to understand business requirements and translate them into technical solutions.
• 5+ years of hands-on experience with the full lifecycle of designing, training, evaluating, testing, and deploying industry-level models.
• Experience building NLP or CV models and integrating them at scale.
• Experience developing complex features/embeddings for downstream models.
• Experience with mainstream DL frameworks: PyTorch or TensorFlow.
• Excitement about working with data and readiness to look behind the metric numbers.
• Experience with our stack (Python, Pytorch, Airflow, BigQuery, Ray, k8s, kafka, GCP)
• Familiarity with the Ads domain and/or Search/Recommender systems is a strong plus.
• Tech leadership experience: mentoring junior engineers and leading complex projects.
• Hands-on experience with using/fine-tuning/building LLMs.
• 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