Staff Research Scientist, AdTech Product Innovation
$200,000–$270,000 year
HybridSan Mateo, California, United States
Job Summary
Design, prototype, and evaluate advanced machine learning and deep learning approaches for recommendation systems, real-time bidding, and LLM-driven applications. Contribute directly through coding, experimentation, and model development across the full ML lifecycle to improve model accuracy, scalability, and efficiency. Partner with engineering and infrastructure teams to deploy, optimize, and monitor machine learning models in large-scale production environments on AWS, GCP, or Azure. Explore emerging technologies in transformers and LLMs to identify practical opportunities within Cognitiv's Deep Learning Advertising Platform. Work cross-functionally with data science, product, and platform teams to solve complex technical challenges and deliver impactful ML solutions.
Required Qualifications
- Master's or Ph.D. in Computer Science, Statistics, Electrical Engineering, or a related field
- 5–7+ years of experience in machine learning R&D or applied ML
- Strong technical expertise in PyTorch, transformers, and Large Language Models (LLMs), including large-scale training, fine-tuning, and optimization of deep neural networks
- Strong understanding of both deep learning and traditional ML techniques (e.g., XGBoost, PCA), with the ability to apply the right approach to the right problem
- Proficiency in Python with strong foundations in algorithms, data structures, and software engineering principles
- Experience building models in real-time, high-throughput systems (e.g., recommender systems, adtech)
- Hands-on experience developing, deploying, and optimizing machine learning models in production environments, including distributed systems, cloud platforms (AWS, GCP, Azure), and big data frameworks (Hadoop, Spark)
- Strong written and verbal communication skills with the ability to work effectively across research and engineering teams in a fast-paced environment
- Location: Bellevue, WA office with a hybrid work schedule of 3 days in office (Mon/Tue/Wed) and 2 days remote (Thursday/Friday)
Desired Qualifications
- Prior exposure to advertising technology and real-time bidding (RTB) systems
- Familiarity with big data frameworks (Spark, Hadoop) and cloud platforms (AWS, GCP, Azure)
- Strong C++ programming ability alongside Python expertise
- A track record of published research or meaningful contributions to the machine learning community
- Experience translating research ideas into scalable, production-grade machine learning systems
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