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Neuroscience Ai Machine Learning Jobs in Missouri

The position places strong emphasis on responsible AI, including privacy, transparency ... Integrate machine learning models into applications, business processes, and operational workflows.

AI Software Engineer

California, MO · On-site

$136.80 - $299.30/hr

A Bachelor's degree in CS, AI, Machine Learning, or a related field (3+ years of experience required). * Deep expertise in software engineering, AI, ASR, or machine learning. * Proficiency in ...

... Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ... Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ...

Machine Learning Tutor

Columbia, MO · Remote

$18 - $40/hr

... Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ... Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ...

... Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the ... Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson ...

Familiarity with AI-driven systems, tools, or workflows and applying AI/ML concepts to real world products, including experience with the machine learning software development lifecycle from ...

Machine Learning Engineer

California, MO · On-site

$110 - $170/hr

As a Machine Learning Integration Engineer, you will help rapidly prototype, mature, and monitor ML ... Analyze large datasets used for AI/ML model development * Identify opportunities to improve AI/ML ...

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Neuroscience Ai Machine Learning information

What is a Neuroscience AI Machine Learning specialist?

A Neuroscience AI Machine Learning specialist is a professional who applies artificial intelligence and machine learning techniques to analyze and interpret data related to the brain and nervous system. They work at the intersection of neuroscience, computer science, and data science to develop models that can help understand brain function, diagnose neurological disorders, or advance brain-computer interface technologies. Their work often involves processing complex datasets such as brain imaging or neural recordings, and building predictive models that contribute to both scientific discovery and healthcare innovation.

What are the key skills and qualifications needed to thrive as a Neuroscience AI Machine Learning specialist?

To thrive as a Neuroscience AI Machine Learning Specialist, you need a strong background in neuroscience, machine learning, and data analysis, often supported by an advanced degree in a related field (e.g., neuroscience, computer science, or bioinformatics). Expertise in programming languages like Python or MATLAB, familiarity with deep learning frameworks (such as TensorFlow or PyTorch), and experience with neuroimaging tools are typically required. Strong problem-solving abilities, curiosity, and effective interdisciplinary communication are valuable soft skills. These competencies are essential for innovatively analyzing complex neural data and developing AI-driven solutions that advance neuroscience research.

What are common challenges faced by professionals working in Neuroscience AI and Machine Learning, and how can they be addressed?

Professionals in Neuroscience AI and Machine Learning often encounter challenges such as integrating complex neural data with AI models, handling large and noisy datasets, and ensuring their algorithms are interpretable and clinically relevant. Collaborating closely with neuroscientists, clinicians, and data engineers is essential to address these hurdles. Staying updated on the latest research, leveraging robust data preprocessing techniques, and participating in interdisciplinary team meetings can help overcome these challenges and contribute to innovative solutions in the field.

What is the difference between Neuroscience Ai Machine Learning vs Data Scientist?

AspectNeuroscience Ai Machine LearningData Scientist
Required CredentialsBackground in neuroscience, AI, machine learning, programming skillsDegree in data science, statistics, computer science, or related fields
Work EnvironmentResearch labs, healthcare, biotech, academiaTech companies, finance, marketing, healthcare
Industry UsageNeuroscience research, AI development for brain-related applicationsData analysis, predictive modeling, business insights across industries

Neuroscience Ai Machine Learning focuses on applying AI and machine learning techniques specifically to neuroscience research and brain-related applications, often requiring specialized knowledge in neuroscience. Data Scientists have a broader scope, working with data analysis and modeling across various industries. While both roles involve machine learning skills, their focus areas and work environments differ significantly.

What are popular job titles related to Neuroscience Ai Machine Learning jobs in Missouri?

For Neuroscience Ai Machine Learning jobs in Missouri, the most frequently searched job titles are:

What cities in Missouri are hiring for Neuroscience Ai Machine Learning jobs?

Cities in Missouri with the most Neuroscience Ai Machine Learning job openings:

Infographic showing various Neuroscience Ai Machine Learning job openings in Missouri as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Machine Learning Specialist

Remote

Contractor

This job post has expired 1 day ago. Applications are no longer accepted.


Job description

This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Machine Learning Specialist based in Netherlands.

This is a remote opportunity for an experienced Machine Learning Specialist to design and deliver data-driven products and AI solutions.
You will work across machine learning, data science, analytics, and predictive modeling to solve complex business challenges.
The role combines hands-on technical delivery with collaboration across data, engineering, analytics, and project teams.
You will transform large and complex datasets into actionable insights, models, reports, and intelligent applications.
There is also an opportunity to influence broader AI initiatives by providing technical guidance and helping shape analytical products.
The position places strong emphasis on responsible AI, including privacy, transparency, accountability, and ethical data practices.
It is well suited to a technically strong professional who enjoys turning advanced analytics into practical business outcomes.

Accountabilities
  • Design, develop, train, validate, and evaluate machine learning models for business and enterprise use cases.
  • Analyze large and complex datasets to identify meaningful patterns, generate insights, and support data-driven decision-making.
  • Prepare, clean, normalize, structure, and organize data for predictive and prescriptive modeling.
  • Develop analytical models, data products, dashboards, reports, and visualizations that communicate findings effectively.
  • Integrate machine learning models into applications, business processes, and operational workflows.
  • Gather, clarify, and document business and technical requirements for AI and analytics initiatives.
  • Collaborate closely with data engineers, analysts, developers, and project teams to deliver end-to-end data solutions.
  • Provide technical leadership, guidance, and expertise across data science and AI initiatives.
  • Support the development of full-stack analytics and AI applications when required.
  • Promote responsible AI practices by considering privacy, accountability, transparency, security, and ethical implications throughout the development lifecycle.
  • Identify, communicate, and appropriately escalate technical risks, dependencies, and issues within a multi-vendor environment.
  • Develop and share reusable analytical models, methodologies, and data products to improve organizational capabilities.
Requirements
  • 6+ years of professional experience using statistical and programming languages for data analysis, machine learning, and related quantitative work.
  • 6+ years of experience designing and implementing analytical and quantitative models.
  • 6+ years of experience preparing and transforming data for predictive and prescriptive modeling.
  • 6+ years of experience applying AI and machine learning techniques to real-world business or enterprise challenges.
  • Strong understanding of data analysis methodologies, statistical techniques, predictive modeling, and machine learning concepts.
  • Demonstrated ability to work with large, complex datasets and translate analytical results into practical recommendations.
  • Strong programming and analytical capabilities, with the ability to develop robust, maintainable data and ML solutions.
  • Experience collaborating effectively with multidisciplinary teams, including data engineers, analysts, developers, and project stakeholders.
  • Ability to understand business requirements and translate them into appropriate technical and analytical approaches.
  • Strong communication skills, with the ability to explain complex technical concepts clearly to both technical and non-technical audiences.
  • A responsible and thoughtful approach to AI development, with awareness of privacy, transparency, accountability, and ethical AI principles.
  • Ability to work independently, manage priorities, provide technical guidance, and escalate risks effectively in a complex delivery environment.
Benefits
  • Fully remote working arrangement.
  • Opportunity to work on AI, machine learning, analytics, and data-driven enterprise initiatives.
  • Exposure to complex business problems and large-scale datasets.
  • Cross-functional collaboration with data, engineering, analytics, and project teams.
  • Opportunity to provide technical leadership and influence the development of analytical data products.
  • Environment focused on responsible, transparent, and ethical use of AI.
How Jobgether works:
We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Our system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company. The final decision and next steps (interviews, assessments) are managed by their internal team.
We appreciate your interest and wish you the best!
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