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Machine Learning Neuroscience Jobs in Seattle, WA

Ai2

Research Engineer, Asta

Seattle, WA · On-site

... neuroscience, social science, etc. • Designing, building, and training machine learning or language models for agentic workflows. • Bridging the gap between cutting-edge research and a widely ...

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Machine Learning Neuroscience information

See Seattle, WA salary details

$29K

$48.5K

$100.1K

How much do machine learning neuroscience jobs pay per year?

As of May 29, 2026, the average yearly pay for machine learning neuroscience in Seattle, WA is $48,461.00, according to ZipRecruiter salary data. Most workers in this role earn between $37,000.00 and $52,300.00 per year, depending on experience, location, and employer.

What is a Machine Learning Neuroscience job?

A Machine Learning Neuroscience job involves using machine learning techniques to analyze and model neural data, helping to understand brain function or improve neurotechnology. Professionals in this field work at the intersection of artificial intelligence, neuroscience, and data science, often developing algorithms to interpret neural signals or enhance brain-computer interfaces. Roles can be found in academia, healthcare, and tech industries, contributing to research, diagnosis, or neuroadaptive systems. Strong skills in programming, statistics, and neuroscience fundamentals are typically required.

What are the key skills and qualifications needed to thrive in the Machine Learning Neuroscience position, and why are they important?

To thrive in a Machine Learning Neuroscience role, you need a solid background in neuroscience, advanced machine learning methods, statistical analysis, and preferably a graduate degree in a related field. Experience using programming languages such as Python or MATLAB, along with tools like TensorFlow, PyTorch, and neuroimaging platforms, is highly desirable. Strong analytical thinking, effective communication, and the ability to work collaboratively across interdisciplinary teams are vital soft skills. These competencies enable professionals to develop impactful models, interpret complex brain data, and drive innovative research or clinical applications in neuroscience.

What are the typical daily tasks and team dynamics for someone working in a Machine Learning Neuroscience role?

In a Machine Learning Neuroscience position, your daily activities might include designing and running algorithms on neurological datasets, interpreting results, refining models, and collaborating with neuroscientists and clinicians. You’ll often work closely with cross-functional teams, contributing technical expertise to research studies or healthcare projects. Regular team meetings, data discussions, and collaborative problem-solving are a central part of the work environment. This collaborative structure fosters innovative ideas and ensures that machine learning approaches are well-suited to real-world neuroscience challenges.
More about Machine Learning Neuroscience jobs
What are the most commonly searched types of Machine Learning Neuroscience jobs in Seattle, WA? The most popular types of Machine Learning Neuroscience jobs in Seattle, WA are:
What are popular job titles related to Machine Learning Neuroscience jobs in Seattle, WA? For Machine Learning Neuroscience jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Machine Learning Neuroscience jobs in Seattle, WA look for? The top searched job categories for Machine Learning Neuroscience jobs in Seattle, WA are:
Machine Learning Neuroscience jobs near you
Infographic showing various Machine Learning Neuroscience job openings in Seattle, WA as of May 2026, with employment types broken down into 4% Full Time, 87% Part Time, 6% Contract, 2% Nights, and 1% Summer. Highlights an 41% Physical, 56% Hybrid, and 3% Remote job distribution, with an average salary of $48,461 per year, or $23.3 per hour.
Research Engineer, Asta

Research Engineer, Asta

Ai2

Seattle, WA • On-site

Full-time

Posted 16 days ago

Job description

Job Summary:
Ai2 is a Seattle based non-profit AI research institute focused on building breakthrough AI to solve the world’s biggest problems. They are seeking a Research Engineer to develop AI tools for scientific discovery and build infrastructure for agentic research, contributing to various domains such as biology and neuroscience.
Responsibilities:
• Building infrastructure to facilitate the next generation of LLM and agentic research.
• Creating AI tools to facilitate scientific discovery in domains such as biology, cancer research, neuroscience, social science, etc.
• Designing, building, and training machine learning or language models for agentic workflows.
• Bridging the gap between cutting-edge research and a widely adopted product.
• Bringing software engineering best practices to a research environment.
• Supporting and collaborating with an open-source community.
• Releasing your contributions back to the broader community in the form of open source software, model releases, and additions to Ai2’s public API and open research datasets, as well as technical reports.
Qualifications:
Required:
• A bachelor’s degree in CS/EE/Data Science/Applied Mathematics/Statistics/ML/NLP, or a related field, or equivalent relevant experience, and expertise in building ML infrastructure.
• 2+ years of experience building agentic infrastructure that handles tools, skills, and other artifacts.
• 2+ years of experience building infrastructure that handles data preprocessing/transformation and machine learning model training, evaluation, inference, and deployment.
• Knowledge of modern deep learning, natural language processing, and reinforcement learning techniques.
• Strong software engineering skills, particularly around building performant systems and debugging.
• Must have experience with Python and PyTorch/Jax/Tensorflow, agentic frameworks (e.g., MCP), as well as feel at ease in picking up new programming languages, libraries, or APIs as tools as project needs evolve.
• Familiarity with cloud compute resources (e.g., GCP, AWS, Modal) and containerization (e.g., Docker).
• Strong collaboration and communication skills - our environment is small and collaborative, and we'd like you to thrive while working closely with others, sometimes with complementary skills/perspectives.
Preferred:
• Advanced degree in CS/EE/Data Science/Applied Mathematics/Statistics/ML/NLP or related fields and/or relevant and equivalent engineering experience.
• Contributions to open-source ML or research libraries (e.g., spaCy, AllenNLP, transformers, langchain).
• Experience successfully operating at scale in a production setting.
• Experience in HPC settings.
• Curiosity about AI research.
Company:
We are a Seattle-based non-profit AI research institute founded in 2014 by the late Paul Allen. Founded in 2014, the company is headquartered in Seattle, USA, with a team of 201-500 employees. The company is currently Growth Stage.

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