Senior Manager, ML Research Science

Are you ready to revolutionize the advertising industry?

At Cognitiv, we are not just another AdTech company— we are industry trailblazers redefining media buying with our Deep Learning Advertising Platform. Since 2015, we have harnessed the power of cutting‑edge deep learning technology and data science to transform how brands connect with their customers. Our mission? To bring intelligence to advertising and deliver unparalleled precision, relevance, and impact at scale.

With our innovative platform, advertisers enjoy unprecedented flexibility—whether it is activating Dynamic Deals through their preferred DSP, leveraging our managed service DSP, or utilizing our industry‑first Context

GPT product. As a part of Cognitiv, you will be at the forefront of AI‑driven advertising solutions, driving change and achieving remarkable growth in a rapidly evolving industry.

Now, we’re growing!

We are seeking a technical leader who can balance strategic leadership with hands‑on contributions. You’ll oversee a growing team of ML research scientists, guide innovation in deep learning and LLMs, and directly advance Cognitiv’s real‑time bidding and recommendation systems. This role is critical to our success, sitting at the intersection of cutting‑edge research and production‑scale delivery.

This position will be located in San Mateo, CA with a hybrid work schedule of 3 days in office (Mon/Tue/Wed) and 2 days remote (Thursday/Friday).

• Lead and Mentor: manage and grow a team of Machine Learning Research Scientists, fostering a collaborative, innovative environment while mentoring individuals on both technical challenges and career development.
• Set Strategic Direction: define and execute the vision for machine learning research within the adtech domain, representing the team in strategic discussions and contributing to company‑wide initiatives.
• Drive Technical Innovation: oversee the design and implementation of cutting‑edge deep learning architectures, staying current with LLM research and guiding the integration of new breakthroughs into Cognitiv’s solutions.
• Stay Hands‑On: actively contribute through coding, experimentation, and code reviews, ensuring technical excellence and adherence to best practices.
• Advance AdTech Performance: continuously improve models and algorithms to drive ad targeting, real‑time bidding performance, and audience relevance.
• Enable Scalable Systems: collaborate with operations, engineering, and cross‑functional partners to refine data pipelines, model deployment, and monitoring systems.
• Deliver Results: manage project timelines, resources, and deliverables, ensuring successful completion of high‑impact research initiatives.

• Core Tools – Python, PyTorch, deep learning architectures (transformers, recommendation models).
• Traditional ML – XGBoost, PCA.
• Big Data / Infra – Spark, Hadoop, distributed training systems.
• Cloud Platforms – AWS, GCP, or Azure.
• Bonus – C++

• Experienced Leader with Advanced
  
  Education:
  
  Master’s or Ph.D. in Computer Science, Statistics, Electrical Engineering, or a related field, with 5–7+ years of experience in machine learning R&D. Proven experience leading teams of researchers and senior ICs/PhDs while remaining 30–50% hands‑on (coding, reviews, experimentation).
• Deep Learning, LLMs & Model Tuning:
  Deep technical expertise in PyTorch, transformers, and Large Language Models (LLMs), including large‑scale training and fine‑tuning of deep neural networks.
• Machine Learning Breadth:
  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.
• Engineering Excellence:
  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).
• Production
  
  Experience:
  
  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 Communicator:
  Excell…