Lead Machine Learning Engineer, Ads Research

Lead Machine Learning Engineer, Ads Research

Location:

Seattle, Washington, United States;
Santa Monica, California, United States;
Glendale, California, United States

This position will be responsible for working across multiple machine learning areas with primary focus on specialization in generative AI applications, including generative mixed media, language models, and other agentic multimodal technologies. Areas of work may include generative video, generative image, generative audio, chatbots, LLM applications, and mixed agentic workflows. Work will additionally include traditional machine learning applications as well, including development of classical ML models to optimize advertisement marketplace operations.

Our mission is to advance AI and machine learning capabilities across Ad Platform by delivering scalable, high impact AI/ML and data science solutions that enhance generative advertisement creation and enhancement, as well as supporting efforts in more traditional AI application spaces such as Ad marketplace optimization, forecasting, and related ML and generative AI experimentation.

We are seeking a Lead Machine Learning Engineer to join this innovative team. This role offers a unique leadership opportunity for an experienced ML engineer who thrives at the intersection of technical excellence, emerging technology, strategic impact, and cross‑functional collaboration, across both generative AI and traditional ML applications.

• Develop, optimize, and product ionize innovative technologies in generative AI (mixed media, video, and agentic LLM applications) as well as in traditional ML modeling applications.
• Create, evaluate, improve, and optimize technologies.
• Drive innovation and apply state of the art AI and machine learning across advertising domains, including inventory forecasting, ad experience, ad pacing, pricing, targeting, and efficient ad delivery.
• Invent and iterate on novel solutions to complex advertising challenges with rapid prototyping and deployment cycles.
• Design, build, and scale robust ML systems that power core ad platform capabilities.
• Champion engineering excellence through best practices in code quality, system design, and operational reliability.
• Mentor and support junior engineers, fostering a culture of continuous learning and technical growth.

• Bachelor’s in computer science or equivalent experience.
• Prior experience rigorously developing, researching, and/or product ionizing any of the following generative AI modeling or AI-based editing domains: image, video, mixed media, audio, LLMs, or agentic flows.
• Experience creating ML datasets (especially in computer vision or generative AI) or developing rigorous quality evaluation processes or data labeling processes, with appreciation for the importance of rigorous quality evaluation.
• Experience developing language-processing applications via LLMs or agentic flows.
• Experience in rapid creative prototyping with generative AI is a plus, such as examples of rapid development of creative generative AI prototyping in research labs, hackathons, etc.
• Minimum 7 years of hands‑on experience developing and deploying large‑scale machine learning systems.
• Strong knowledge of AI/ML technologies, mathematics and statistics.
• Excellent communication, collaboration skills, and a strong teamwork ethic with both technical and non‑technical audiences.
• Strong foundations in algorithms, data structures, and numerical optimization with experience in programming languages such as Python (primary), Java and SQL.
• Familiarity with deep learning tools and frameworks such as Tensor Flow, PyTorch, JAX, Hugging Face libraries, etc.
• Expert knowledge with traditional (tabular) ML modeling and methods.
• Proven proficiency in deep learning methodologies, fine‑tuning, and transformer architectures.
• A proven track record of thriving in a fast‑paced, data‑driven, and collaborative work environment.
• Experience working closely with UX and front‑end designers building production generative AI products.

• MS or PhD (preferred) in computer science or equivalent experience.
• Experience with multimodal models and embedding…