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Cognitive Science Jobs in Seattle, WA (NOW HIRING)

Dlapiper

Data Scientist

Seattle, WA · On-site +1

A specialization in machine-learning, artificial intelligence, cognitive science or data science is preferred. Must be self-driven, curious and creative. * Experience must include creating and using ...

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Cognitive Science information

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$26.7K

$65.3K

$87.1K

How much do cognitive science jobs pay per year?

As of Sep 3, 2026, the average yearly pay for cognitive science in Seattle, WA is $65,338.00, according to ZipRecruiter salary data. Most workers in this role earn between $54,600.00 and $70,600.00 per year, depending on experience, location, and employer.

What is a cognitive science job?

A Cognitive Science job involves applying knowledge from psychology, neuroscience, artificial intelligence, philosophy, and linguistics to understand how humans and machines think, learn, and process information. Professionals in this field work in diverse industries, including technology, healthcare, research, and user experience design. Common roles include data scientist, UX researcher, AI specialist, and cognitive psychologist. These jobs often require analytical thinking, programming skills, and expertise in human behavior or machine learning.

What are the key skills and qualifications needed to thrive in a cognitive science position?

To thrive in a Cognitive Science role, you need a solid grounding in psychology, neuroscience, computer science, linguistics, and data analysis, usually supported by at least a bachelor's or master's degree in a related field. Familiarity with statistical analysis software (such as SPSS or R), programming languages (like Python or MATLAB), and research tools is highly advantageous. Outstanding collaboration, critical thinking, and clear communication skills set top candidates apart in multidisciplinary teams. These skills and qualifications enable professionals to analyze complex cognitive processes and contribute innovative solutions to real-world human-computer interaction, AI, or behavioral research challenges.

What are the typical career progression opportunities for someone in a cognitive science role?

Professionals in cognitive science often start in research assistant, data analyst, or user experience roles and can progress to positions such as lead researcher, UX researcher, cognitive engineer, or even project manager depending on their interests and expertise. With experience and additional qualifications, some transition into roles in artificial intelligence, human-computer interaction, neurotechnology, or higher education as professors or principal investigators. Opportunities for advancement are often influenced by your ability to publish research, collaborate across disciplines, and acquire advanced degrees or certifications. Many cognitive science professionals also find pathways into related industries including technology, healthcare, and education, allowing for diverse and rewarding career trajectories.

Is cognitive science a useful degree?

Cognitive science is a versatile degree that prepares graduates for careers in research, technology, healthcare, and user experience design by combining psychology, neuroscience, computer science, and linguistics. It develops skills in critical thinking, data analysis, and problem-solving, which are valuable across many industries. Job opportunities often require interdisciplinary knowledge and may benefit from programming skills or familiarity with AI tools.

Is cognitive science in demand?

Cognitive science is a growing interdisciplinary field with increasing demand in areas such as artificial intelligence, human-computer interaction, and user experience design. Professionals with skills in data analysis, programming, and understanding of cognitive processes are sought after in research, technology, and healthcare sectors.

What does a cognitive scientist do?

A cognitive scientist studies mental processes such as perception, memory, language, and decision-making by analyzing how the brain and mind work. They often conduct experiments, develop models, and use tools like neuroimaging to understand human cognition, working in research, academia, or applied settings. Strong analytical skills and knowledge of psychology, neuroscience, and computer science are essential for this role.

What are the most commonly searched types of Cognitive Science jobs in Seattle, WA?

The most popular types of Cognitive Science jobs in Seattle, WA are:

What are popular job titles related to Cognitive Science jobs in Seattle, WA?

For Cognitive Science jobs in Seattle, WA, the most frequently searched job titles are:

What job categories do people searching Cognitive Science jobs in Seattle, WA look for?

The top searched job categories for Cognitive Science jobs in Seattle, WA are:

What cities near Seattle, WA are hiring for Cognitive Science jobs?

Cities near Seattle, WA with the most Cognitive Science job openings:

Cognitive Science jobs near you
Infographic showing various Cognitive Science job openings in Seattle, WA as of August 2026, with employment types broken down into 1% As Needed, 77% Full Time, 19% Part Time, and 3% Contract. Highlights an 79% Physical, 3% Hybrid, and 18% Remote job distribution, with an average salary of $65,338 per year, or $31.4 per hour.

Machine Learning Engineer, Human Centered AI - Evaluations & Insights

Socket.dev

Seattle, WA • On-site

$150 - $190/hr

Other

Posted 4 days ago

Job description

Imagine what you could do here. At Apple, great new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish! Are you passionate about music, movies, and the world of Artificial Intelligence and Machine Learning? So are we! Join our Human-Centered AI team for Apple Media Services. In this role, you'll represent the user perspective on new features, review and analyze data, and evaluate AI models powering everything from search and recommendations to other innovative features. You'll also collaborate with Data Scientists, Researchers, and Engineers to drive improvements across our platforms.

Description

We are looking for a Machine Learning Engineer focused on Evaluation & Insights for the Human-Centered AI team. In this role, you will bridge the gap between human perception and algorithmic performance, helping evaluate and optimize Foundation Models and generative AI systems. You will architect robust evaluation frameworks, design scalable MLOps pipelines for model assessment, and translate qualitative failure modes into programmatic guardrails and training signals (e.g., SFT, RLHF/DPO). This role blends deep ML engineering expertise with strong analytical judgment to assess, interpret, and improve the behavior of advanced AI models. You will work cross-functionally with Software Engineering, Product, Research and Responsible AI teams at Apple to ensure that our AI experiences are reliable, safe, and aligned with human expectations.

Minimum Qualifications
  • 5+ years of relevant industry experience in ML Engineering or Applied Research.
  • Advanced proficiency in Python and modern deep learning ecosystems (PyTorch, JAX, Hugging Face).
  • Proven experience building scalable ML inference pipelines, model-evaluation workflows, and structured rating frameworks for large-scale AI systems.
  • Strong ability to interpret unstructured model outputs (text, transcripts, embedding spaces) and synthesize qualitative findings into actionable engineering guidance and training objectives.
  • Hands-on experience developing, fine-tuning, or evaluating LLMs, multimodal models, and NLP systems.
  • Deep familiarity with AI quality metrics, hallucination detection techniques (e.g., SelfCheckGPT), model alignment (RLHF/DPO), and LLM-as-a-judge frameworks (e.g., G-Eval, DeepEval).
  • Experience building internal tools or automated pipelines for ML workflows using tools like MLflow, Weights & Biases, or similar platforms.
  • Strong familiarity with advanced prompt engineering, RAG architectures (vector databases, semantic search), and Fine-Tuning.
  • Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, Cognitive Science, or a related technical field
Preferred Qualifications
  • Knowledge of human factors, HCI, or cognitive science methodologies as applied to AI system design.
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