data
Posted 2 hours agoSenior Machine Learning Engineer, Ads Foundational Representations
at Redditinc
NetherlandsRemote
Responsibilities
- Building data processing and inference pipelines for the models we develop.
Requirements
- With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit is one of the internet’s largest sources of information.
- We are a Machine Learning/Data heavy team with a focus on the following areas:
- LLM-based Representations - Leveraging LLMs, VLMs, and foundational models to build complex representations of Reddit entities that improve ranking outcomes
- As a Senior ML Engineer , you’ll be in charge of the full-cycle execution of ML projects - from collaborating with cross-functional teams on
- Ensuring the reliability, scalability, and performance of the ML systems by writing automated tests, monitoring performance, and implementing best practices for model management.
- 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.
- 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 with using/fine-tuning/building LLMs. Required
- In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI).
Experience
- 5+ years of hands-on
Benefits
- Gender-Affirming Care
- Private Pension plan with Employer-matching
- Flexible Vacation & Paid Volunteer Time Off
- Generous Paid Parental Leave
Contact
- For more information, visit www.redditinc.com .
Additional details
- It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet.
- Location: Reddit has a flexible first workforce. Don't live near our office? No worries: you can work remotely from anywhere in the UK or the Netherlands.
- We work on building embeddings to understand content and users' interests based on the content they engage with.
- 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.
- The signals and features we create become a key piece in the Ads Delivery funnel, from targeting to the auction, as well as the Business Insights product and other advertiser-facing products such as Creative generation and optimization.
- requirements and design, to the implementation of the feature and its experimentation. Responsibilities
- 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.