Staff Research Scientist, AdTech Product Innovation
Quick Summary
Are you ready to revolutionize the advertising industry? At Cognitiv,
We are seeking a Staff Research Scientist who can drive innovation through deep technical expertise and hands-on execution. You’ll contribute to cutting-edge research in deep learning and LLMs while advancing Cognitiv’s real-time bidding and recommendation systems at production scale. This role sits at the intersection of applied research and high-performance machine learning systems.
Location: This position will be located in Bellevue, WA office with a hybrid work schedule of 3 days in office (Mon/Tue/Wed) and 2 days remote (Thursday/Friday).
Responsibilities
~1 min read- →Drive Research & Innovation. Design, prototype, and evaluate advanced machine learning and deep learning approaches, with a focus on recommendation systems, real-time bidding, and LLM-driven applications.
- →Stay Hands-On. Contribute directly through coding, experimentation, model development, and technical problem-solving across the full ML lifecycle.
- →Advance AdTech Performance. Improve model accuracy, scalability, and efficiency to drive ad targeting, bidding performance, and audience relevance.
- →Build Production-Ready ML Systems. Partner closely with engineering and infrastructure teams to deploy, optimize, and monitor machine learning models in large-scale production environments.
- →Explore Emerging Technologies. Stay current with advancements in deep learning, transformers, and LLM research, identifying practical opportunities to apply new techniques within Cognitiv’s platform.
- →Collaborate Cross-Functionally. Work closely with data science, engineering, product, and platform teams to solve complex technical challenges and deliver impactful ML solutions.
- →Contribute Technical Expertise. Provide thoughtful technical input through design discussions, experimentation reviews, and collaboration with other researchers and engineers.
- 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 ML Researcher/Engineer: 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 or applied ML.
- Deep Learning & LLM Expertise: Strong technical expertise in PyTorch, transformers, and Large Language Models (LLMs), including large-scale training, fine-tuning, and optimization 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).
- Collaborative Communicator: Strong written and verbal communication skills with the ability to work effectively across research and engineering teams in a fast-paced environment.
Nice to Have
~1 min read- 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 Production. Experience translating research ideas into scalable, production-grade machine learning systems.
Salary: $200,000 - $270,000 USD Base Salary + Equity
What We Offer
~1 min read- Festiv – We make work fun with cross-team games, events, and creative team bonding.
- Responsiv – You’ll be close to clients and leadership, influencing real outcomes.
- Inclusiv – Diversity and individuality are celebrated across all levels.
- Inventiv – We reward curiosity and embrace bold ideas.
- Transformativ – We support your growth with training, mentorship, and flexibility.
- Collaborativ – We operate across coasts, connected by purpose and teamwork.
Location & Eligibility
Listing Details
- Posted
- July 20, 2026
- First seen
- July 20, 2026
- Last seen
- July 21, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 67%
- Scored at
- July 20, 2026
Signal breakdown
Please let Cognitiv know you found this job on Jobera.
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