Director, ML Research Science; Adtech​/Recommender Systems

The Role

We are seeking a technical leader who can balance strategic leadership with hands‑on contributions. You will 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 (Thu/Fri).

• 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 ad‑tech 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 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, ad‑tech).
• 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: Excellent written and verbal communication skills, strong project management capabilities, and the ability to drive alignment in fast‑paced, dynamic environments.

• AdTech & RTB Experience.
• Distributed Systems & Cloud.
• C++ Skills.
• Research & Community Impact.
• Bridging Research and Delivery.

$250,000 – $330,000 USD Base Salary + Equity.

• Medical, Dental and Vision plan for US employees & Extended Health Benefits for Canadian employees.
• 12 weeks paid parental leave + 4 weeks WFH.
• Unlimited PTO + Work‑From‑Anywhere August.
• Career development with clear advancement paths.
• Equity for all employees.
• Hybrid work model & daily team lunch.
• Health & wellness stipend + cell phone reimbursement.
• 401(k) & RRSP with employer match.
• Parking (CA, WA, Vancouver offices) & pre‑tax commuter benefits.
• Employee Assistance Program.
• Comprehensive onboarding (Cognitiv University).

• Festi…