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Ai In Government Jobs in Santa Rosa, CA (NOW HIRING)

We are especially interested in candidates who are deeply fluent in the use of large language ... The successful candidate will contribute to multiple government-funded and institutional research ...

Coordinate legal, regulatory, and government affairs initiatives with external counsel * Support ... Experience in startup, venture-backed, or venture studio environments * Daily user of AI tools such ...

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Coordinate legal, regulatory, and government affairs initiatives with external counsel * Support ... Experience in startup, venture-backed, or venture studio environments * Daily user of AI tools such ...

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... in the fields of sensor science, signal processing, data fusion, artificial intelligence (AI ... Collaborate with government personnel, shipyards, original equipment manufacturers, and ...

... in E-Verify and will provide the federal government with your Form I-9 information to confirm that ... intelligence (AI) tools to support parts of the hiring process, such as reviewing applications ...

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Ai In Government information

How is AI used in government work?

AI in government work involves automating administrative tasks, analyzing large data sets for policy development, and improving public services such as healthcare, transportation, and security. Government agencies often employ data analysis tools, machine learning algorithms, and natural language processing to enhance decision-making and operational efficiency.

What is the difference between Ai In Government vs Data Analyst in Government?

AspectAi In GovernmentData Analyst in Government
Required CredentialsDegree in Computer Science, Data Science, or related fields; knowledge of AI/ML toolsDegree in Statistics, Mathematics, or related fields; proficiency in data analysis software
Work EnvironmentDeveloping and implementing AI models within government agenciesAnalyzing government data sets to inform policy and decision-making
Employer & Industry UsagePrimarily in tech-focused government projects and agenciesAcross various government departments for data-driven insights

Ai In Government roles focus on creating and deploying AI solutions within government settings, requiring technical expertise in AI/ML. Data Analysts in Government interpret data to support policy and operational decisions. While both roles work within government, Ai In Government emphasizes AI development, whereas Data Analysts focus on data interpretation and reporting.

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$60K - $75K/yr

Full-time

Medical, Retirement, PTO

Re-posted 29 days ago


Job description

Position Summary
The Buck Institute for Research on Aging is seeking an exceptional, highly motivated AI Data Scientist / Agentic AI Engineer to join a collaborative research team focused on aging, computational biology, multi-omics, and translational data science.
This position is ideal for a creative, technically outstanding individual with a Master's degree or equivalent experience who has demonstrated excellence through high-impact projects, awards, hackathons, publications, startup experience, open-source contributions, or other evidence of exceptional technical ability. We are especially interested in candidates who are deeply fluent in the use of large language models, agentic AI systems, modern software engineering practices, and scalable approaches for harmonizing and modeling large, complex datasets.
The successful candidate will contribute to multiple government-funded and institutional research initiatives, including a recently launched, government-funded project focused on using large-scale human data to better understand biological aging, resilience, healthspan, and age-related disease risk. This role will help develop innovative AI-enabled systems for organizing, harmonizing, analyzing, modeling, and interpreting large datasets generated across multiple collaborators, institutions, platforms, and data types.
We are looking for someone who is not only technically strong, but also inventive, entrepreneurial, and capable of rapidly building solutions. The ideal candidate will be comfortable working at the intersection of AI, software engineering, data science, and biomedical research, and will bring the creativity needed to design new approaches for managing and modeling complex scientific data.
Key Responsibilities
1. Develop AI-enabled systems for large-scale data harmonization and modeling
The candidate will help design, build, and implement computational systems that support the organization, harmonization, modeling, and interpretation of large biomedical datasets. Responsibilities may include:
  • Developing agentic AI workflows to support data curation, quality control, documentation, and analysis
  • Designing LLM-powered tools to help harmonize large datasets across cohorts, studies, institutions, and assay platforms
  • Building pipelines to extract, standardize, and validate metadata and data dictionaries
  • Creating systems to support multi-modal data integration across omics, clinical, demographic, imaging, and functional datasets
  • Developing scalable approaches for identifying patterns, inconsistencies, and missing information across large datasets
  • Supporting model development for prediction, classification, clustering, and biological interpretation
  • Prototyping AI tools that improve research productivity, reproducibility, and scientific discovery
2. Apply LLMs, agentic AI, and modern machine learning approaches to biomedical research
Responsibilities may include:
  • Building workflows using large language models, retrieval-augmented generation, vector databases, tool-calling agents, and automated reasoning systems
  • Designing AI agents capable of interacting with structured and unstructured scientific data
  • Developing systems that assist with literature mining, data annotation, hypothesis generation, and biological interpretation
  • Evaluating the performance, limitations, and reliability of AI-enabled tools in biomedical research contexts
  • Supporting responsible, reproducible, and well-documented use of AI in federally funded research
  • Collaborating with bioinformaticians and domain experts to translate research needs into functional computational tools
3. Support large-scale data science and computational biology projects
The candidate may contribute to analyses involving:
  • Transcriptomics, including single-cell and bulk RNA-seq
  • Proteomics
  • Metabolomics
  • Epigenetics and biological aging clocks
  • Clinical and phenotypic datasets
  • Survey data
  • Integrative multi-omics
  • Dimensionality reduction and clustering
  • Classification methods and predictive modeling
  • Drug repurposing
  • Network analysis and pathway enrichment
  • Computer vision and feature extraction, as applicable
4. Collaborate across interdisciplinary teams
The candidate will work closely with computational biologists, data scientists, principal investigators, research staff, software engineers, and external collaborators. Responsibilities may include:
  • Translating scientific goals into computational tools and workflows
  • Participating in project meetings and presenting technical progress
  • Creating clear documentation, diagrams, and technical specifications
  • Supporting manuscript preparation, grant writing, figure generation, and reporting
  • Working with diverse teams to improve data transfer, management, and analysis systems
  • Helping establish best practices for AI-assisted data science in biomedical research

Qualifications
Required Education and Experience
  • Master's degree in Computer Science, Data Science, Computational Biology, Bioinformatics, Applied Mathematics, Statistics, Engineering, or a related field; equivalent professional, entrepreneurial, or technical experience will also be considered
  • Demonstrated experience building AI, data science, machine learning, or software engineering systems
  • Strong proficiency in Python
  • Experience using large language models, AI APIs, or LLM-based developer tools
  • Experience with modern software engineering practices, version control, testing, documentation, and collaborative development
  • Ability to work independently, rapidly prototype solutions, and solve ambiguous technical problems
Required Skills
  • Strong practical experience with large language models and AI-assisted workflows
  • Interest or experience in agentic AI, tool-calling agents, retrieval-augmented generation, vector search, or automated workflow orchestration
  • Strong analytical and problem-solving skills
  • Ability to design systems for organizing, harmonizing, and modeling large datasets
  • Comfort working with structured and unstructured data
  • Excellent written and oral communication skills
  • Strong attention to detail and commitment to reproducibility
  • Ability to collaborate with both technical and non-technical team members
  • High degree of creativity, initiative, and intellectual curiosity
Preferred Qualifications
  • Evidence of exceptional technical achievement, such as hackathon wins, awards, competitive programming, startup experience, open-source contributions, publications, deployed products, or other high-impact projects
  • Experience with biomedical, healthcare, clinical, or omics data
  • Experience with APIs, cloud platforms, Docker, databases, or scalable data systems
  • Experience with vector databases, embeddings, RAG systems, or AI agent frameworks
  • Experience with Python-based data science libraries and machine learning frameworks
  • Familiarity with data harmonization, metadata standards, ontologies, or research data repositories
  • Experience working in fast-paced startup, academic, or highly collaborative environments

Compensation and Benefits
  • Salary range: $60,000-$75,000, commensurate with experience
  • Full-time position
  • Exciting, collaborative work environment at the forefront of aging research, AI, and computational biology
  • Opportunity to help build AI-enabled systems for large-scale biomedical discovery
  • Generous benefits package, including:
    • Health insurance
    • Paid parental leave
    • Generous paid time off
    • 401(k) with 5% employer match
  • Work visa sponsorship may be available for qualified candidates

About the Buck Institute
Our success will ultimately change healthcare. At the Buck Institute for Research on Aging, we aim to end the threat of age-related diseases for this and future generations by bringing together the most capable and passionate scientists from a broad range of disciplines to identify and impede the ways in which we age.
The Buck is an independent, nonprofit institution located in Marin County, California, with the goal of increasing human healthspan, or the healthy years of life. Globally recognized as a pioneer and leader in efforts to target aging - the number one risk factor for diseases including Alzheimer's disease, Parkinson's disease, cancer, macular degeneration, heart disease, and diabetes - the Buck seeks to help people live better longer.
We are an equal opportunity employer and strive to create an atmosphere where diversity of identity, experience, and background are welcomed, valued, and supported. Candidates who contribute to this diversity are strongly encouraged to apply.
To Apply
Interested candidates should click the Apply button to complete the online application.
Please upload:
  1. Resume or CV
  2. A brief statement describing your technical interests, relevant AI/data science experience, and examples of systems, tools, or projects you have built
  3. Names and contact information for three references, if available