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Hourly Large Language Model Llm Jobs in Michigan

Midlevel AI Developer

Ann Arbor, MI · On-site

$50 - $55/hr

Ann Arbor, MI Salary: $50.00 USD Hourly - $55.00 USD Hourly Description: Our client is currently ... Experience with Large Language Model (LLM) platforms (e.g., OpenAI, Anthropic Claude, Azure OpenAI ...

We are seeking a Principal AI Engineer with deep, hands-on experience in Large Language Models ... Lead the design, development, and deployment of LLM-based automation solutions across multiple ...

Software Engineer

Detroit, MI · On-site

  • Medical

  • Retirement

Experience working with large language model (LLM) APIs or generative AI systems * Experience designing and building scalable systems in Azure or other cloud platforms * Experience with Kubernetes ...

Data and AI Engineer

Ann Arbor, MI · On-site

$112K - $134K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

Familiarity with large language model (LLM) APIs and AI tool deployment * Experience with Linux/Unix environments for research computing * Experience working with sensitive and confidential data ...

Hands-on experience building applications with large language models - prompt engineering, RAG, tool/function calling, and agentic workflows. * Experience with LLM platforms and APIs such as Claude ...

Hands-on experience building applications with large language models - prompt engineering, RAG, tool/function calling, and agentic workflows. * Experience with LLM platforms and APIs such as Claude ...

Java AI Engineer

Farmington Hills, MI · On-site

$51 - $69.75/hr

Experience with large language models is a must. Machine learning frameworks, or AI cloud services ... Experience with OpenAI or similar LLM frameworks * Familiarity with Streamlit, FastAPI, or Flask ...

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Hourly Large Language Model Llm information

What is an hourly large language model LLM?

Hourly Large Language Model (LLM) jobs are roles where individuals work with LLMs, such as ChatGPT or similar AI systems, on an hourly basis. These positions often involve tasks like data annotation, prompt engineering, AI model evaluation, or content generation. Workers may be responsible for improving AI responses, testing models, or creating training data. The 'hourly' aspect means they are paid based on the number of hours worked, rather than a fixed salary or per-project rate. Such jobs are common in tech companies, research organizations, or freelance platforms.

What are the key skills and qualifications needed to thrive as a large language model (LLM) engineer?

To thrive as a Large Language Model (LLM) Engineer, you need a solid background in machine learning, natural language processing, and programming—typically with a degree in computer science or a related field. Experience with frameworks like TensorFlow or PyTorch, familiarity with cloud platforms, and knowledge of model deployment tools are highly valued, along with certifications in AI or data science. Strong problem-solving skills, creativity, and effective communication help you collaborate with cross-functional teams and innovate solutions. These competencies are crucial for developing, optimizing, and scaling LLMs to meet evolving business and research needs.

What are some common challenges faced by hourly large language model (LLM) annotators and how can they be addressed?

Hourly LLM annotators often face challenges such as maintaining consistency in labeling, handling ambiguous or unclear data, and managing the repetitive nature of annotation tasks. To address these challenges, it's helpful to regularly review annotation guidelines, participate in team discussions to clarify uncertainties, and leverage available feedback from quality assurance checks. Collaborating with teammates and project managers can also provide support and ensure alignment on task expectations, making the work environment more collaborative and improving overall accuracy.

What is the difference between Hourly Large Language Model Llm vs Data Scientist?

AspectHourly Large Language Model LlmData Scientist
Required CredentialsKnowledge of AI, NLP, programming skillsDegree in Data Science, Statistics, or related field
Work EnvironmentTech companies, AI research labs, freelance projectsCorporate, consulting firms, research institutions
Industry UsageDeveloping and fine-tuning language models, AI applicationsData analysis, predictive modeling, data visualization

While both roles involve working with data and advanced technology, Hourly Large Language Model Llm focuses on developing and deploying AI language models, whereas Data Scientists analyze data to inform business decisions. The roles share skills in programming and data handling but differ in their primary objectives and work environments.

What are the most commonly searched types of Large Language Model Llm jobs in Michigan?

The most popular types of Large Language Model Llm jobs in Michigan are:

What are popular job titles related to Hourly Large Language Model Llm jobs in Michigan?

For Hourly Large Language Model Llm jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Hourly Large Language Model Llm jobs in Michigan look for?

The top searched job categories for Hourly Large Language Model Llm jobs in Michigan are:

What cities in Michigan are hiring for Hourly Large Language Model Llm jobs?

Cities in Michigan with the most Hourly Large Language Model Llm job openings:

Staff AI/ML Engineer (Large Language Model) (TS/SCI) {S}

Danbury Mission Technologies

Lewiston, MI • On-site

Full-time

Re-posted 17 days ago


Job description

Job Summary:
Danbury Mission Technologies is an advanced technologies company serving the U.S. military and intelligence community. The Staff AI/ML Engineer will lead the development of Agentic AI capabilities and other LLM based capabilities for mission management applications.
Responsibilities:
• Lead and mentor a multidisciplined team consisting of developers and researchers to implement machine learning algorithms to solve a broad set of challenges for our various customers
• Lead and mentor a multidisciplinary team delivering advanced AI/ML solutions
• Apply LLMs to complex domain-specific problems and operational workflows
• Adapt and fine-tune foundation models for specialized use cases
• Design and implement retrieval-augmented generation (RAG) systems and semantic search architectures
• Build production-grade LLM applications and agentic systems
• Deploy scalable AI solutions across cloud, on-prem, and hybrid environments
• Analyze large, multi-modal datasets to extract meaningful features and actionable insights
• Translate emerging research into applied, mission-relevant capabilities
• Communicate technical strategy, status, and risks to internal and external leadership
Qualifications:
Required:
• B.S. in machine learning, computer science, mathematics, or related fields
• 8+ years of experience, preferably in software development or as a data scientist with 2+ years of building LLM applications using some of the following: Fine-tuning foundational models, Steering Techniques (e.g Sparse auto encoders, representation tuning), Building adapters to use foundational models (e.g. PEFT, llama factory), Prompt engineering techniques / Inference time techniques (e.g. chain of thought, tree of thoughts, etc.), Using Retrieval Augmented Generation techniques to populate and query vector databases (e.g. Weaviate, pinecone, pgvector), Using LLM Frameworks (e.g. LangChain, DSPy, Microsoft Agent Framework), Using AI APIs ( e.g AWS Bedrock, OpenAI), Using LLM deployment frameworks (eg llama.cpp, vllm, tgi), Developing UIs with ReAct
• Experience leading an interdisciplinary team of researchers and software developers and working with a program manager to define project scope and schedule to ensure we meet project milestones as defined by our customers
• Experience with Python and data science / machine learning libraries (e.g. NumPy, Pandas, Polars, scikit-learn, etc.)
• Experience contributing on a team using version control (e.g. git, GitLab, Bitbucket)
• Active TS/SCI U.S. Government Security Clearance
Preferred:
• M.S. or PhD in machine learning, computer science, mathematics, or related fields
• Experience leading an interdisciplinary team of researchers and software developers
• Experience with any of the following: Large Language Models and experience identifying ways to incorporate them into new domains and applications
• Applying Transformer-based architectures to domains in other areas outside of Natural Language Processing (NLP) such as computer vision
• Natural Language Processing algorithms such as BERT
• Reinforcement learning and familiarity with Gymnasium Gym, OpenEnv, TorchRL, RLlib, and Stable Baselines
• Applying clustering algorithms and/or deep neural networks to real life problems
• Implementing tracking and pattern-of-life algorithms
• Experience with GenAI Ops techniques (e.g. LLM-as-a-judge) and frameworks (e.g. LangFuse, MLFlow, Arize Phoenix)
• Experience with Machine Learning libraries and frameworks such as HuggingFace and LangChain
• Experience with Linux
• Experience with CUDA and Python libraries such as CuPy, Numba, CuSignal, CuDF, etc.
• Familiarity with using AWS cloud computing resources such as EC2, S3, Lambda, etc.
• Experience with any of the following additional languages: Java, C++, Rust, Go, and/or C#
• Experience in application deployment, virtualization, and containerization (e.g. Podman, Docker, Kubernetes, Rancher)
• Experience shaping and writing proposals
• Adjudicated Counter Intelligence or Full Scope Polygraph
Company:
This page is no longer active. Visit ARKA.org. Founded in , the company is headquartered in Danbury, Connecticut, US, , with a team of 501-1000 employees. The company is currently Late Stage.