Machine Learning Engineer

Job Title: Senior Machine Learning Engineer – Research Location: Santa Monica, CA or Seattle, WA (4 days/week onsite – no remote) Employment Type: 24-month contract Pay Rate: $97/hour Overview A large-scale digital advertising technology organization is seeking a Senior Machine Learning Engineer to join its AI/ML research team. This group is responsible for building and evolving high-performance, distributed, microservice-based advertising platforms that support video and digital media experiences at scale. The team’s mission is to advance machine learning and AI capabilities across advertising systems by delivering scalable, high-impact solutions that improve ad decisioning, forecasting, experimentation, and overall ad experience.

This role is well suited for an experienced ML engineer who enjoys working on complex problems, influencing technical direction, and collaborating across engineering, product, and data science teams. Key Responsibilities Apply state-of-the-art machine learning and AI techniques across advertising domains such as forecasting, targeting, pacing, pricing, ad experience, and delivery optimization Design, prototype, and deploy novel ML solutions to complex, real-world problems with rapid iteration cycles Architect, build, and scale production-ready ML systems that support core platform capabilities Promote engineering best practices related to code quality, system design, testing, and operational reliability Mentor junior engineers and contribute to a culture of technical excellence and continuous learning Required Qualifications Bachelor’s degree in Computer Science, Information Systems, or a related field (or equivalent practical experience) 3+ years of hands‑on experience building and deploying large-scale machine learning systems Strong foundation in machine learning, statistics, mathematics, and numerical optimization Proficiency in Python (primary), with working knowledge of Java and SQL Solid understanding of algorithms and data structures Experience with ML frameworks and libraries such as TensorFlow, PyTorch, and Hugging Face Hands‑on experience with deep learning models, including sequence‑based and recurrent architectures Experience working with transformer models (e.g., BERT‑like, GPT‑like, vision transformers) Knowledge of multimodal embeddings spanning text, image, audio, and structured data Experience with large language models (e.g., GPT‑style, Claude‑style, Llama‑style models) Familiarity with LLM evaluation techniques and retrieval‑augmented generation (RAG) architectures Strong communication skills and the ability to collaborate effectively with both technical and non-technical stakeholders Proven ability to succeed in a fast‑paced, data‑driven, collaborative environment Preferred Qualifications (Nice to Have) Master’s or PhD in Computer Science or a related field Exposure to Databricks and/or AWS SageMaker #J-18808-Ljbffr