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.
Requirements
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.
Tech Stack
PyTorch
Tensorflow
Benefits
Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support