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Ai Rag Jobs in Kentucky (NOW HIRING)

Senior Applied AI Engineer

Louisville, KY · On-site +1

$100K - $137K/yr

Deploy and maintain AI systems across Databricks and Microsoft Azure services such as Azure ... Familiarity with RAG architecture, vector databases, or agentic orchestration. * Familiarity with ...

Senior Applied AI Engineer

Louisville, KY · On-site +1

$100K - $137K/yr

Deploy and maintain AI systems across Databricks and Microsoft Azure services such as Azure ... Familiarity with RAG architecture, vector databases, or agentic orchestration. * Familiarity with ...

Senior Applied AI Engineer

Louisville, KY · On-site +1

$100K - $137K/yr

Deploy and maintain AI systems across Databricks and Microsoft Azure services such as Azure ... Familiarity with RAG architecture, vector databases, or agentic orchestration. * Familiarity with ...

Senior Applied AI Engineer

Louisville, KY · On-site

$100K - $137K/yr

Deploy and maintain AI systems across Databricks and Microsoft Azure services such as Azure ... Familiarity with RAG architecture, vector databases, or agentic orchestration. * Familiarity with ...

Design and implement systems leveraging LLMs, RAG, agentic AI frameworks, knowledge graphs, and advanced machine learning techniques * Build AI agents and autonomous workflows capable of supporting a ...

Red-team the enterprise's own AI-LLM-powered products, agents, RAG pipelines, and ML applications, against prompt injection, jailbreaks, model extraction and inversion, membership inference, data and ...

Red-team the enterprise's own AI-LLM-powered products, agents, RAG pipelines, and ML applications, against prompt injection, jailbreaks, model extraction and inversion, membership inference, data and ...

Run red-team operations and test the enterprise's own AI. Objective-driven adversary emulation; and adversarial assessment of internal LLM-powered products, agents, RAG pipelines, and ML applications ...

Run red-team operations and test the enterprise's own AI. Objective-driven adversary emulation; and adversarial assessment of internal LLM-powered products, agents, RAG pipelines, and ML applications ...

Run red-team operations and test the enterprise's own AI. Objective-driven adversary emulation; and adversarial assessment of internal LLM-powered products, agents, RAG pipelines, and ML applications ...

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Ai Rag information

What are the key skills and qualifications needed to thrive as an AI Researcher, and why are they important?

To thrive as an AI Researcher, you need a strong background in computer science, mathematics, and machine learning, usually with an advanced degree such as a Master's or Ph.D. Proficiency with programming languages like Python, deep learning frameworks (e.g., TensorFlow, PyTorch), and familiarity with scientific research tools is essential. Critical thinking, creativity, and effective collaboration are vital soft skills for generating novel ideas and working in multidisciplinary teams. These skills and qualities are crucial to drive innovation and solve complex problems in the rapidly evolving field of artificial intelligence.

What is the difference between Ai Rag vs Data Analyst?

AspectAi RagData Analyst
Required CredentialsTypically a diploma or certification in AI, machine learning, or related fieldsBachelor's degree in statistics, mathematics, or related fields
Work EnvironmentTech companies, AI startups, research labsBusiness, finance, healthcare, and various industries
Employer & Industry UsagePrimarily in AI development and researchAcross industries for data interpretation and decision-making
Common Search & ComparisonYesYes

Ai Rag and Data Analyst roles share overlapping skills in data handling and analysis, but Ai Rag focuses more on AI-specific applications and machine learning, while Data Analysts concentrate on interpreting data to inform business decisions. Both roles are vital in data-driven industries, with Ai Rag often working in AI development environments and Data Analysts supporting strategic insights across sectors.

Which AI is best at RAG?

For an AI Rag role, the best AI systems for Retrieval-Augmented Generation (RAG) tasks typically include models like OpenAI's GPT-4, Google's Bard, and Meta's Llama 2, which are capable of integrating retrieval components with language generation. Success in RAG depends on the model's ability to efficiently access and incorporate external data, as well as the implementation of effective retrieval mechanisms and fine-tuning. Skills in natural language processing, knowledge of retrieval systems, and experience with relevant tools are essential for this role.

What engineer makes 500,000 a year?

Senior software engineers, especially those working in high-demand fields like artificial intelligence or machine learning at large tech companies, can earn $500,000 or more annually. Compensation often includes base salary, bonuses, and stock options, and requires advanced skills, extensive experience, and often a master's or Ph.D. in a related field.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-paying position in artificial intelligence, such as senior machine learning engineer, AI research director, or executive roles like AI CTO. These roles often require advanced skills in data science, deep learning, and experience with tools like TensorFlow or PyTorch, along with a strong track record of innovation and leadership in the field.

What are AI RAGs?

AI RAGs, or Retrieval-Augmented Generation systems, are a type of artificial intelligence that combines the power of retrieving information from large databases or documents with generating human-like text responses. This approach allows AI models to provide more accurate, up-to-date, and contextually relevant answers by referencing external data sources during the generation process. RAGs are commonly used in applications like chatbots, search engines, and customer support systems, where comprehensive and factual responses are important.

Which 3 jobs will survive AI?

AI Rag is a role that involves managing and interpreting AI outputs, and jobs that require complex problem-solving, creativity, and emotional intelligence are more likely to survive AI automation. Examples include healthcare professionals, skilled tradespeople, and roles in education. These jobs often require human judgment, interpersonal skills, and adaptability that AI cannot fully replicate.

What are some common challenges faced by AI RAG (Retrieval-Augmented Generation) engineers when integrating retrieval systems with large language models?

AI RAG engineers often encounter challenges such as ensuring seamless integration between retrieval systems and language models, maintaining low latency for real-time responses, and handling the quality and relevance of retrieved data. Additionally, tuning the system to balance retrieval accuracy with generative fluency can be complex, especially when dealing with large or unstructured datasets. Collaboration with data engineers, ML researchers, and product teams is essential to address these challenges and optimize system performance.
What are popular job titles related to Ai Rag jobs in Kentucky? For Ai Rag jobs in Kentucky, the most frequently searched job titles are:
What cities in Kentucky are hiring for Ai Rag jobs? Cities in Kentucky with the most Ai Rag job openings:

$125K/yr

Other

Posted 6 days ago

New


Job description

WHAT IS INFORMATION TECHNOLOGY?
A description of the business units can be found at: https://www.jobs.irs.gov/about/who/business-divisions
  • Position(s) are to be filled in following area(s): Information Technology.
  • Consider each location carefully when applying. If you are selected for a location, that location will become your official post of duty.

REVIEW THE ADDITIONAL INFORMATION BELOW FOR FURTHER DETAILSQualifications:

Federal experience is not required. Experience may have been gained in the public sector, private sector or through Volunteer Service. One year of experience refers to full-time work; part-timework is considered on a prorated basis. To ensure full credit for your work experience, please indicate dates of employment by month/day/year, and indicate number of hours worked per week, on your resume.
You must meet the following requirements by the closing date of this announcement.
QUALIFICATION REQUIREMENTS: To qualify for this position, you must meet the qualification requirements outlined below:
BASIC REQUIREMENTS All GRADES: Applicants must have Information Technology related experience demonstrating each of the following four competencies: 1) Attention to Detail, 2) Customer Service, 3) Oral Communication, and 4) Problem Solving.
Minimum requirements for Grade 12 and up (GS or Equivalent) Applicants must have Information Technology related experience demonstrating each of the following nine competencies: 1) Attention to Detail, 2) Customer Service, 3) Decision Making, 4) Information Management, 5) Interpersonal Skills, 6) Oral Communication, 7) Problem Solving, 8)Team Work and 9) Technical Competence.
EDUCATION: A degree in mathematics, statistics, computer science, data science, or field directly related to the position. The degree must be in a major field of study (at least at the baccalaureate level) that is appropriate for the position.
OR
COMBINATION OF EDUCATION AND EXPERIENCE: A combination of education and experience that includes courses equivalent to a major field of study (30 semester hours) as shown in the paragraph above, plus additional education or appropriate experience.
AND
SPECIALIZED EXPERIENCE GRADE 14: In addition to the basic requirements, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-13 grade level in the Federal service. Specialized experience for this position includes:

  • Experience designing, developing, deploying, and supporting Artificial Intelligence (AI), Machine Learning (ML), Generative AI, and advanced analytics solutions in production environments.
  • Experience applying statistical analysis, hypothesis testing, experimental design, predictive modeling, model evaluation, and data science techniques to solve business problems and support data-driven decision making.
  • Experience developing, validating, deploying, monitoring, and continuously improving machine learning and AI models, including model performance evaluation, explainability, governance, and responsible AI practices.
  • Experience working with large-scale structured and unstructured data using cloud platforms, distributed computing environments, and big data technologies such as Databricks, Apache Spark, Azure, AWS, Google Cloud Platform (GCP), or similar technologies.
  • Experience designing and optimizing Natural Language Processing (NLP), Large Language Model (LLM), prompt engineering, retrieval-augmented generation (RAG), intent classification, and conversational AI solutions.
  • Experience integrating AI, analytics, and enterprise applications, APIs, databases, cloud services, authentication systems, and knowledge management solutions.
  • Experience developing and maintaining data pipelines, data processing frameworks, and cloud-based analytics solutions to support AI model development, operational reporting, and business intelligence initiatives.
  • Experience analyzing customer interactions, operational data, performance metrics, and user behavior to identify trends, improve AI effectiveness, enhance customer experience, and optimize business operations.
  • Experience applying data governance, data quality, privacy, security, compliance, and responsible AI principles throughout the data and analytics lifecycle.
  • Experience using programming languages such as Python, Java, SQL, Scala, or similar technologies to develop applications, automation solutions, data pipelines, APIs, and AI-enabled services.
  • Experience applying DevSecOps, CI/CD pipelines, automated testing, version control, and agile development practices to support reliable and secure deployment of AI and analytics solutions.
  • Experience developing dashboards, reports, data visualizations, and performance metrics that communicate analytical findings and support executive and operational decision making.
  • Experience translating business, program, and operational requirements into technical solutions and actionable recommendations while collaborating with stakeholders, engineers, data scientists, architects, cybersecurity teams, and leadership.

AND
You must also meet the following requirement(s):

  • PERFORMANCE RATING: Current federal employees must have at least a fully successful or equivalent performance rating to receive consideration.
  • TIME AFTER COMPETITIVE APPOINTMENT (TACA): By the closing date (or if this is an open continuous announcement, by the cut-off date) specified in this job announcement, current civilian employees must have completed at least 90 days of federal civilian service since their latest non-temporary appointment from a competitive referral certificate, known as time after competitive appointment. For this requirement, a competitive appointment is one where you applied to and were appointed from an announcement open to "All US Citizens"
  • TIME IN GRADE (TIG): Federal employees must meet time-in-grade requirements. For positions above the GS-05,applicants must meet applicable time-in-grade requirements to be considered eligible. One year (52 weeks) at the next lower grade level is required to meet the time-in-grade requirements for the grade you are applying for. For positions at the GS-05, you cannot advance to the GS-05 if you have held a GS-02 in the past 52 weeks. There is no TIG restriction for GS-02, 03, or 04 positions.

For more information on qualifications please refer to OPM's Qualifications Standards.

Education:A college or university degree generally must be from an accredited (or pre-accredited) college or university recognized by the U.S. Department of Education. For a list of schools which meet these criteria, please refer to Department of Education Accreditation page.
FOREIGN EDUCATION: Education completed in foreign colleges or universities may be used to meet the requirements. You must show proof the education credentials have been deemed to be at least equivalent to that gained in conventional U.S. education program. It is your responsibility to provide such evidence when applying. Click here (Section 3, Explanation of Terms) or here for Foreign Education Credentialing instructions.
We recommend choosing an evaluator from a member organization of one of the following national associations of credential evaluation services: National Association of Credential Evaluation Services (NACES) or Association of International Credentials Evaluators (AICE).Employment Type: OTHER