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Llm Developer Jobs in Novi, MI (NOW HIRING)

We are seeking a Senior AI Validation Engineer to design and implement testing strategies ... Develop automated test pipelines for LLM-based features, including hallucination detection ...

Experience PreferredExperience integrating with LLM inference APIs or AI engine backends ... Google Cloud Professional Cloud Developer certification.Familiarity with OpenAPI specification and ...

Java Developer

Dearborn, MI · On-site

$47 - $60.75/hr

Experience PreferredPractical experience building or integrating Generative AI solutions, including LLM-based applications, RAG pipelines, prompt engineering, embeddings, and vector databases.

Java Developer

Dearborn, MI · On-site

$47 - $60.75/hr

Experience Preferred Practical experience building or integrating Generative AI solutions, including LLM-based applications, RAG pipelines, prompt engineering, embeddings, and vector databases.

Build evaluation harnesses (golden datasets, LLM-as-judge, regression suites) using AgentCore ... Hands-on experience with Amazon Bedrock and/or AgentCore as a developer: runtime, gateways, memory ...

Build evaluation harnesses (golden datasets, LLM-as-judge, regression suites) using AgentCore ... Hands-on experience with Amazon Bedrock and/or AgentCore as a developer: runtime, gateways, memory ...

Build evaluation harnesses (golden datasets, LLM-as-judge, regression suites) using AgentCore ... Hands-on experience with Amazon Bedrock and/or AgentCore as a developer: runtime, gateways, memory ...

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Llm Developer information

See Novi, MI salary details

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How much do llm developer jobs pay per hour?

As of Aug 15, 2026, the average hourly pay for llm developer in Novi, MI is $47.06, according to ZipRecruiter salary data. Most workers in this role earn between $36.97 and $57.07 per hour, depending on experience, location, and employer.

What does an LLM Developer do?

An LLM Developer designs, fine-tunes, and implements large language models (LLMs) for various applications, such as chatbots, content generation, and AI-driven tools. They work with machine learning frameworks, optimize model performance, and ensure efficient deployment. This role requires expertise in natural language processing (NLP), deep learning, and programming languages like Python.

What are the key skills and qualifications needed to thrive as an LLM Developer?

To excel as an LLM Developer, you need strong expertise in natural language processing (NLP), deep learning frameworks, and programming languages such as Python, typically supported by a degree in computer science or a related field. Familiarity with machine learning libraries (like TensorFlow or PyTorch), cloud computing platforms, and experience with prompt engineering or fine-tuning large language models is crucial. Excellent problem-solving abilities, collaboration, and effective communication skills help you design solutions and work efficiently within multidisciplinary teams. These qualifications are essential for successfully building, deploying, and optimizing large language models that drive impactful AI applications.

What is the role of a Llm developer?

A Large Language Model (LLM) developer designs, trains, and fine-tunes large-scale AI models for natural language processing tasks. They work with machine learning frameworks, handle large datasets, and optimize models for performance and accuracy, often requiring knowledge of programming languages like Python and tools such as TensorFlow or PyTorch.

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Infographic showing various Llm Developer job openings in Novi, MI as of August 2026, with employment types broken down into 77% Full Time, 9% Part Time, and 14% Contract. Highlights an 80% Physical, 6% Hybrid, and 14% Remote job distribution, with an average salary of $97,895 per year, or $47.1 per hour.

AI Validation Engineer

Stellantis

Auburn Hills, MI • On-site

Full-time

Posted 9 days ago


Stellantis rating

7.5

Company rating: 7.5 out of 10

Based on 130 frontline employees who took The Breakroom Quiz

14th of 44 rated automakers


Job description

As AI-powered features become central to automotive vehicles - from ADAS perception and voice assistants to predictive diagnostics and intelligent infotainment - rigorous validation of these systems is critical for successful deployment. We are seeking a Senior AI Validation Engineer to design and implement testing strategies, frameworks, and automated pipelines that ensure the quality, safety, and reliability of deep learning and LLM-based features across vehicle platforms.
This role sits at the intersection of AI/ML engineering and automotive system validation. You will build the tools, datasets, and evaluation methodologies that enable confident delivery of AI-driven automotive solutions.
Key Responsibilities:
  • Design and implement validation frameworks for deep learning models (perception, NLP, generative AI) deployed in automotive systems, covering accuracy, robustness, latency, and safety metrics.
  • Develop automated test pipelines for LLM-based features, including hallucination detection, response quality evaluation, prompt regression testing, and adversarial input testing.
  • Build and curate evaluation datasets and benchmarks tailored to automotive AI use cases (e.g., voice commands, diagnostic Q&A, sensor fusion outputs).
  • Create AI-assisted test generation tools that leverage LLMs to automatically produce test cases, test data, and expected-result specifications from system requirements.
  • Develop model monitoring and drift detection systems for AI features running in production and test environments.
  • Collaborate with system architects to integrate AI model validation into existing test bench infrastructure and CI/CD pipelines.
  • Implement automated regression testing for ML model updates, ensuring backward compatibility and performance parity across software releases.
  • Analyze test results using statistical methods and ML techniques to identify root causes, failure patterns, and quality trends.
  • Work in cross-functional Agile teams spanning AI/ML, embedded software, and system integration disciplines.

Basic Qualifications:
  • Bachelor's degree in computer science, Machine Learning, Data Science, Electrical Engineering, or a related field.
  • Minimum of 5 years of experience in ML/AI development, with a minimum of 2 years focused on model evaluation, testing, or validation.
  • Strong proficiency in Python and testing/automation frameworks (pytest, Robot Framework, or equivalent).
  • Hands-on experience evaluating deep learning models - including metrics design, dataset curation, bias/fairness analysis, and regression testing.
  • Experience with LLM evaluation techniques (BLEU, ROUGE, human-in-the-loop evaluation, LLM-as-judge approaches).
  • Familiarity with ML experiment tracking and pipeline orchestration tools (MLflow, Weights & Biases, Kubeflow, or equivalent).
  • Experience with CI/CD systems (Jenkins, GitLab CI, GitHub Actions) for automated test execution.
  • Strong analytical and communication skills with the ability to translate AI validation results into actionable insights for engineering teams.

Preferred Qualifications:
  • Master's in Computer Science, Machine Learning, or a related field.
  • Experience with simulation-based testing or digital twin environments.
  • Familiarity with automotive test toolchains (dSpace, Vector CANoe, NI VeriStand) is a plus but not required.
  • Ability to collaborate effectively across time zones with global engineering teams.
  • Knowledge of automotive safety standards (ISO 26262, SOTIF/ISO 21448) as applied to AI systems.
  • Experience with adversarial robustness testing, out-of-distribution detection, or uncertainty quantification for neural networks.

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