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Language Model Jobs in Michigan (NOW HIRING)

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Language Model information

What are language models?

Language models are artificial intelligence systems designed to understand, generate, and manipulate human language. They are trained on vast amounts of text data to predict the next word in a sequence, answer questions, write content, translate languages, and perform other language-related tasks. Modern language models, such as those based on deep learning, have revolutionized natural language processing by enabling more accurate and context-aware interactions between humans and machines.

What is the difference between Language Model vs Data Scientist?

AspectLanguage ModelData Scientist
Required CredentialsNone specific; knowledge of NLP and AI concepts helpfulBachelor's or higher in Data Science, Statistics, or related fields
Work EnvironmentAI development teams, research labs, tech companiesBusiness, finance, healthcare, and various industries
Employer & Industry UsageUsed in AI applications, chatbots, content generationAnalyzing data, building models, providing insights

While both roles involve working with data and AI, a Language Model is an AI system designed to understand and generate human language, often developed by AI engineers. A Data Scientist analyzes data to extract insights and build predictive models, often utilizing language models as tools. Understanding the differences helps clarify career paths and job expectations in the AI and data fields.

What are the key skills and qualifications needed to thrive as a Language Model, and why are they important?

To thrive as a Language Model Engineer, you need a strong background in computer science, machine learning, and natural language processing, often supported by a relevant degree. Experience with frameworks like TensorFlow or PyTorch, and familiarity with large-scale data processing tools, are typically required. Strong analytical thinking, collaboration, and problem-solving skills help in designing effective models and working with cross-functional teams. These capabilities are crucial for developing performant and accurate language models that meet complex real-world communication needs.

What are the common challenges faced by professionals working on language model development teams?

Professionals developing language models often encounter challenges such as managing large datasets, addressing biases in training data, and optimizing model performance while balancing computational resources. Collaboration with cross-functional teams—including data scientists, engineers, and domain experts—is essential to ensure the model's accuracy and relevance. Additionally, staying current with rapid advancements in AI research and maintaining responsible AI practices are crucial aspects of the role.
What cities in Michigan are hiring for Language Model jobs? Cities in Michigan with the most Language Model job openings:
Lead Data Scientist (Artificial Intelligence/Machine Learning)

Lead Data Scientist (Artificial Intelligence/Machine Learning)

US Department of the Treasury

Marquette, MI • On-site

$125K/yr

Other

Posted 5 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

223rd of 668 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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