Director, ML Research Science (Adtech / Recommender Systems)

About the role

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.

Location

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).

What You'll Do

• 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.

Tech Stack

• 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++.

Who You Are

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

Bonus Points If You Have

• AdTech & RTB Experience. Prior exposure to advertising technology and real-time bidding (RTB) systems is a strong plus.
• Distributed Systems & Cloud. Familiarity with big data frameworks (Spark, Hadoop) and cloud platforms (AWS, GCP, Azure).
• C++ Skills. Strong C++ programming ability is a significant advantage alongside Python expertise.
• Research & Community Impact. A track record of published research or meaningful contributions to the machine learning community.
• Bridging Research and Delivery. Experience managing both exploratory research timelines and production-grade delivery cycles.

Salary

$250,000 - $330,000 USD Base Salary + Equity

What We Offer

• 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)

Note on AI Use

Cognitiv may use AI technology to assist with certain administrative aspects of the hiring process, such as note-taking, interview documentation, and reporting. However, every resume and application is reviewed directly by our recruiting team. AI tools are used solely for operational support and do not influence candidate evaluation or hiring decisions.