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AI/ML Engineer

BESTPEGASUS LLCMinnesota City, MN🇺🇸United StatesPosted Sep 28, 2026

Why This Role Stands Out

You'll have the opportunity to shape cutting-edge AI solutions for a renowned automotive leader, gaining invaluable experience in Generative AI and MLOps. This hybrid role is perfect for seasoned AI/ML Engineers with a strong Python and cloud platform background who thrive on innovation and collaboration. Apply now to advance your career in a dynamic and impactful field.

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
Minnesota City, MN, United States
Posted
20 hours ago
DockerSQLAWSMLOpsMachine LearningNLPScikit-learnAzureDeep LearningGenerative AIGitGoogle CloudHugging FaceKubernetesLLMPyTorchPythonTensorFlow

Job Description

Title: AI/ML Engineer
Location:  Minnesota & Connecticut  
Duration: 12 Months
Client: General Motors
Experience: 8+ Years 
MOI: Virtual    

Job Description:
We are looking for an experienced AI/ML Engineer with 8+ years of experience in designing, developing, and deploying Machine Learning and Artificial Intelligence solutions. The ideal candidate 
should have strong expertise in Machine Learning, Deep Learning, Generative AI, and cloud-based AI platforms.
Required Skills:


  • 8+ years of experience in AI/ML development. 

  • Strong programming skills in Python and SQL. 

  • Experience with Machine Learning and Deep Learning frameworks such as TensorFlow, PyTorch, and Scikit-learn. 

  • Hands-on experience with Generative AI, Large Language Models (LLMs), and Retrieval-Augmented Generation (RAG). 

  • Experience with NLP, predictive analytics, and model optimization.
  •  
    Knowledge of MLOps, model deployment, and monitoring. 

  • Experience with AWS, Azure, or Google Cloud Platform cloud platforms. 

  • Familiarity with Docker, Kubernetes, and Git. 
  • Responsbilities:
    Develop, train, and deploy AI/ML models. 
    Build Generative AI and NLP-based solutions. 
    Collaborate with cross-functional teams to deliver AI-driven applications. 
    Optimize model performance and scalability. 
    Implement MLOps best practices for model deployment and maintenance.
    Preferred:
    Experience with LangChain, Hugging Face, Vector Databases, and LLM fine-tuning. 

  • AI/ML cloud certifications are a plus.

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