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Language Model Jobs in Michigan (NOW HIRING)

This role centers on designing, building, and optimizing intelligent agent architectures powered by large language models (LLMs) and advanced reasoning frameworks. The ideal candidate brings a strong ...

This role centers on designing, building, and optimizing intelligent agent architectures powered by large language models (LLMs) and advanced reasoning frameworks. The ideal candidate brings a strong ...

Machine Learning Engineer

Dearborn, MI

$105K - $126K/yr

Employees in this job function are responsible for designing, building, deploying, and scaling complex self-running ML solutions -- including Generative AI and Large Language Model (LLM) systems ...

Large language models (LLMs) and generative AI applications, machine learning models, natural language processing (NLP), optimization and mathematical programming and recommendation systems. * Builds ...

Large language models (LLMs) and generative AI applications, machine learning models, natural language processing (NLP), optimization and mathematical programming and recommendation systems. * Builds ...

Large language models (LLMs) and generative AI applications, machine learning models, natural language processing (NLP), optimization and mathematical programming and recommendation systems. * Builds ...

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

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

Danbury Mission Technologies

Lewiston, MI • On-site

Full-time

Posted 5 days ago


Job description

Job Summary:
Danbury Mission Technologies is an advanced technologies company serving the U.S. military and intelligence community. The Principal AI/ML Engineer will support the development of AI/ML algorithms across various disciplines, leading a team to implement solutions for complex challenges.
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
• Apply Large Language Models (LLMs) to a variety of applications within remote sensing such as tasking collections, identifying gaps in collection plans, analyzing patterns of life, and more.
• Fine tune foundation models and building adaptors for new applications (llama factory, PEFT)
• Apply retrieval augmented generation (RAG) techniques to data to populate and query vector databases (e.g. Weaviate)
• Build custom applications with LLM frameworks such as LangChain, DSPy
• Deploy LLM solutions across cloud-based and local resources using kubernetes (llama.ccp, vllm etc)
• Analyze large multi-domain datasets such as images, text and/or graph data, to identify statistically relevant features to build models that provide analysts with actionable data
• Review relevant publications to understand and apply cutting edge concepts to defense and commercial applications
• Interface with both internal and external leadership to communicate technical status
Qualifications:
Required:
• BS in machine learning, computer science, mathematics, or related fields.
• 10+ 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)
• Using LLM Frameworks (e.g. LangChain, DSPy)
• 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. PyTorch, TensorFlow, Keras, OpenCV, NumPy, Pandas, Polars, scikit-learn, etc.)
• Active TS/SCI U.S. Government Security Clearance
Preferred:
• MS 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 Computer Vision domains:
• Large Language Models and experience identifying ways to incorporate them into new areas and applications
• Applying Transformer-based architectures to domains in other areas outside of Natural Language Processing (NLP) such as computer vision
• Object detection algorithms such as YOLO and Faster-RCNN
• Natural Language Processing algorithms such as BERT
• Generative Adversarial Networks and Variational Autoencoders
• Reinforcement learning and familiarity with Gymnasium Gym, 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 Machine Learning libraries and frameworks such as HuggingFace and LangChain
• Experience with Computer Vision libraries such as OpenCV, Nerfstudio, FiftyOne, etc.
• Experience with Linux
• 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 implementing algorithms on the GPU in Python or C++ using CUDA and other CUDA libraries
• Experience with implementing tracking and pattern-of-life algorithms
• Experience in application deployment, virtualization, and containerization (e.g. Podman, Docker, Kubernetes, Rancher)
• Experience working with various Remote Sensing datasets (e.g. EO/OPIR/SAR images, passive RF, etc.)
• Experience shaping and writing proposals
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.