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Associate Artificial Intelligence Machine Learning Jobs in Texas

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Associate Artificial Intelligence Machine Learning information

What are the key skills and qualifications needed to thrive as an Associate Artificial Intelligence Machine Learning professional, and why are they important?

To thrive as an Associate Artificial Intelligence Machine Learning professional, you need a solid background in mathematics, statistics, and computer science, typically with a relevant degree and familiarity with machine learning concepts. Proficiency in programming languages like Python or R, experience with frameworks such as TensorFlow or PyTorch, and knowledge of version control systems are commonly required. Strong problem-solving, analytical thinking, and effective communication skills help differentiate top performers in this role. These skills are crucial for developing accurate models, collaborating with multidisciplinary teams, and driving impactful AI solutions.

What is the difference between Associate Artificial Intelligence Machine Learning vs Data Scientist?

AspectAssociate Artificial Intelligence Machine LearningData Scientist
Required CredentialsBachelor's in CS, AI, or related; certifications in ML/AIBachelor's/Master's in CS, Statistics, or related; often advanced degrees
Work EnvironmentTech companies, R&D labs, startupsData-driven organizations, consulting firms, tech companies
Employer & Industry UsageAI/ML teams, product developmentData analysis, predictive modeling, business insights
Common Search & ComparisonYesYes

Associate Artificial Intelligence Machine Learning roles focus on developing and implementing AI/ML models, often with entry-level responsibilities. Data Scientists analyze data to extract insights, build predictive models, and support decision-making. While both roles require knowledge of programming and statistics, Data Scientists typically have more advanced degrees and focus on data analysis, whereas Associate AI/ML roles are more specialized in AI/ML model development.

What does an Associate Artificial Intelligence Machine Learning professional do?

An Associate Artificial Intelligence Machine Learning (AI/ML) professional assists with the development, testing, and deployment of AI and machine learning models. They typically work under the supervision of senior data scientists or machine learning engineers, helping to preprocess data, select algorithms, and evaluate model performance. Their responsibilities may also include writing code, analyzing results, and supporting the integration of models into applications or systems. This entry-level role is ideal for those who have foundational knowledge in AI/ML concepts and are looking to gain practical, hands-on experience in the field.

What are some common challenges faced by Associate Artificial Intelligence Machine Learning professionals in their first year, and how can they overcome them?

Associate AI/ML professionals often encounter challenges such as understanding complex datasets, adapting to rapidly evolving tools and frameworks, and bridging the gap between theoretical knowledge and practical application. Collaborating closely with senior team members, seeking mentorship, and participating in code reviews are effective ways to overcome these challenges. Additionally, staying updated with industry trends and continuously practicing model building on real-world problems can help associates gain confidence and accelerate their learning curve.
What are the most commonly searched types of Artificial Intelligence Machine Learning jobs in Texas? The most popular types of Artificial Intelligence Machine Learning jobs in Texas are:
What job categories do people searching Associate Artificial Intelligence Machine Learning jobs in Texas look for? The top searched job categories for Associate Artificial Intelligence Machine Learning jobs in Texas are:
Lead Data Scientist (Artificial Intelligence/Machine Learning)

Lead Data Scientist (Artificial Intelligence/Machine Learning)

US Department of the Treasury

Beaumont, TX

$125K/yr

Other

Posted 7 days ago


U.S. Department Of The Treasury rating

8.2

Company rating: 8.2 out of 10

Based on 13 frontline employees who took The Breakroom Quiz

227th of 673 rated public administrative organizations


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):
    • IT - Taxpayer Services and Online Accounts
  • 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.
BASIC REQUIREMENTS All GRADES: EDUCATION:
You must have a bachelor's or higher degree in mathematics, statistics, computer science, data science or other 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.
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:

  • Designing, developing, integrating, testing, and supporting conversational AI solutions, virtual assistants, chatbots, digital messaging platforms, voice automation, interactive voice response (IVR) platforms, or generative AI-enabled customer engagement solutions in a production environment.
  • Developing and optimizing natural language understanding (NLU), natural language processing (NLP), speech recognition, intent classification, entity recognition, conversational workflows, or automated self-service solutions supporting customer interactions across voice and digital channels.
  • Designing, testing, implementing, and refining prompt engineering strategies, generative AI workflows, large language model (LLM) integrations, and AI-assisted customer engagement capabilities to improve automation, containment, customer experience, and operational outcomes.
  • Integrating conversational AI, generative AI, voice, chat, messaging, or digital engagement platforms with enterprise applications, APIs, backend systems, authentication services, customer data platforms, or knowledge management solutions.
  • Demonstrating subject matter expert (SME)-level proficiency in at least one modern programming language such as Java or Python, including development of backend services, automation, integrations, data processing pipelines, or conversational application logic.
  • Analyzing customer interaction data, conversation transcripts, chat sessions, operational metrics, and user behavior to identify trends, improve AI performance, evaluate model effectiveness, and enhance customer experience outcomes.
  • Developing, querying, and analyzing large datasets using cloud-based analytics platforms and data warehouses to support AI model evaluation, operational reporting, and business decision-making.
  • Troubleshooting and resolving complex system integration, application reliability, authentication, speech processing, conversational AI, generative AI, digital engagement, or performance issues across interconnected platforms.
  • Applying DevSecOps, CI/CD pipelines, automated testing, version control, and agile software development practices in enterprise environments.
  • Collaborating with business stakeholders, architects, engineers, cybersecurity personnel, data scientists, and operations teams to translate business requirements into AI-enabled technical solutions.

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

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