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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Senior Machine Learning Engineer, Ads Foundational Representations - **Company:** Reddit - **Location:** Amsterdam, Netherlands (Remote available) - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Airflow, Automation of Tests, BigQuery, Graph Database, Python (Programming Language), Machine Learning, Recommender Systems, Tensorflow, Data Processing, Google Cloud, Pytorch, Large Language Models, Kubernetes, Apache Kafka, Machine Learning Operations - **Published:** June 21, 2026 - **Apply:** https://nl.indeed.com/viewjob?jk=b4d374d1b7f7e38c ## About the Role Do you have a Master's degree?, * 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. Preferred Qualifications: * 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. ## Description * 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 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. 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 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. * 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. ## Related Videos - [Data Science in Retail](https://www.wearedevelopers.com/videos/586-data-science-in-retail) - [DevOps for Machine Learning](https://www.wearedevelopers.com/videos/179-devops-for-machine-learning) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. 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