Manager, Machine Learning Engineering - Ad Platforms

Manager, Machine Learning Engineering – Ad Platforms Job Summary: You will apply your battle‑tested experience, deep technical knowledge of software and systems including Machine Learning and AI technologies, and leadership skills to unblock and guide our ML/AI team members to design and build scalable, performant, maintainable, and testable models and pipelines in various domains using industry best practices aligned with close collaboration with the ML team in the US. Responsibilities: Lead, mentor and guide Data Scientists, Machine Learning and AI engineers to build solutions adhering to industry best practices and deliver scalable solutions including model architecture and algorithm selection. Lead by example and always strive to improve designs for more scalable, cleaner, and decoupled implementations. Drive adoption of best practices in model development, code quality, testing, and documentation. Ensure solid understanding and usage of automated tools while adhering to company policy. Define strategic direction for machine learning projects and collaborate with product and engineering stakeholders. Oversee end‑to‑end machine learning workflow, including data collection, model development, deployment, and modeling, aligned with the larger platform strategy and tools in collaboration with global teams. Foster innovation by exploring new ML techniques, tools, and technologies. Communicate strategies, progress, and results to leadership and cross‑functional teams. Ensure responsible AI practices, including fairness, explainability, and compliance with privacy and ethical standards. Develop partnerships across the organization to identify and prioritize high‑impact ML opportunities. Participate in on‑call rotations based on the team’s escalation policy and support schedule for ML/AI solutions. Basic Qualifications: Bachelor’s or master’s degree in computer science, engineering, mathematics, statistics, or a related field. 8+ years of relevant industry experience, with at least 2–3 years in a people‑management or technical leadership role. Proven ability to translate business problems into scalable ML and GenAI solutions and strong understanding of machine learning fundamentals, deep learning, and statistical modeling. Proven experience designing, building, and deploying scalable machine learning models and systems in production. Experience deploying ML/GenAI systems at scale using cloud platforms and MLOps practices. Advanced programming proficiency (e.g., Python, Java, or similar) and experience with ML/DL frameworks such as TensorFlow, PyTorch, JAX, or Hugging Face. Experience building, fine‑tuning, evaluating, and deploying LLM‑based systems (e.g., RAG, prompt engineering, model optimization). Demonstrated ability to lead global teams and collaborate across organizational boundaries. Preferred Qualifications: Domain knowledge in the Ad Tech industry. Experience working with large‑scale data and distributed systems. Knowledge of cloud platforms (AWS, GCP, Azure) and MLOps pipelines. Track record of innovation and contributions to the ML/AI community (publications, talks, open source). Compensation: Hiring range for this position in Los Angeles, CA area is $171,600 – $230,100 per year and Seattle Area is $179,700 – $241,000. Base pay will be determined based on internal equity, geographic region, job‑related knowledge, skills, and experience. A bonus and/or long‑term incentive units may be offered as part of the compensation package, plus a full range of medical, financial, and other benefits. Location: Seattle, WA, USA #J-18808-Ljbffr