Senior Machine Learning Engineer, Ads Foundational Representations

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.

Required Qualifications

• 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.