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Large Language Model Llm Jobs Near Me

Whiz Global LLC

ML Engineer

Columbus, OH · On-site

This role focuses on engineering production-ready machine learning applications, Large Language Model (LLM) solutions, and cloud-native ML platforms while partnering closely with Data Science teams ...

Whiz Global LLC

ML engineer

Columbus, OH · On-site

Experience building and deploying Large Language Model (LLM) solutions. * Hands-on experience with Amazon Bedrock for LLM development is preferred. Responsibilities * Design, build, deploy, and ...

Wolters Kluwer

Senior Legal Counsel

Columbus, OH · On-site

$134K - $183K/yr

... large language model ("LLM") model training, and/or other emerging artificial intelligence ("AI") technologies, and (v) business associate agreements and/or data processing agreements. * Work closely ...

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How much do large language model llm jobs pay per hour?

As of Aug 2, 2026, the average hourly pay for large language model llm in the United States is $24.34, according to ZipRecruiter salary data. Most workers in this role earn between $18.99 and $29.09 per hour, depending on experience, location, and employer.
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Large Language Model Llm jobs near you
A map of the United States highlighting the number of Large Language Model Llm job openings by state according to ZipRecruiter. The image is accompanied by a detailed chart listing the number of Large Language Model Llm job openings in each state, with California having the most at 2 and Hawaii the least at 0.

ML Engineer

Whiz Global LLC

Columbus, OH • On-site

Other

Posted 9 days ago

Job description

Job Title: ML Engineer (AI/LLM & Cloud)

Location: Jersey City, NJ (Hybrid – 3 Days Onsite) OR Columbus, OH (5 Days Onsite)
Duration: Contract-to-Hire

Job Summary

We are seeking a highly experienced ML Engineer to design, build, deploy, and integrate enterprise-scale AI/ML solutions within the JPMorgan Chase ecosystem. This role focuses on engineering production-ready machine learning applications, Large Language Model (LLM) solutions, and cloud-native ML platforms while partnering closely with Data Science teams and business stakeholders.

The ideal candidate is a hands-on engineer with strong Python expertise, cloud experience, and MLOps knowledge who can lead technical initiatives and deliver scalable AI solutions.

Key Responsibilities
  • Design, develop, deploy, and maintain scalable AI/ML applications.
  • Build production-ready machine learning systems and infrastructure.
  • Productionize machine learning models developed by Data Science teams.
  • Design and deploy Large Language Model (LLM) applications.
  • Integrate AI solutions into AWS and JPMorgan Chase internal cloud platforms.
  • Develop scalable model serving and inference pipelines.
  • Implement CI/CD pipelines for ML applications.
  • Build monitoring, observability, model drift detection, and automated retraining solutions.
  • Optimize AI applications for performance, scalability, reliability, and cost.
  • Collaborate with Product Managers, Data Scientists, Software Engineers, and Business SMEs.
  • Mentor junior engineers and provide technical leadership through architecture guidance and code reviews.
  • Research and implement modern AI/ML technologies and best practices.
Required Qualifications
  • Bachelor''s or Master''s degree in Computer Science, Engineering, Data Science, or a related field.
  • 10+ years of hands-on experience developing and deploying machine learning solutions in production.
  • Expert-level programming experience with Python.
  • Basic understanding of Java or Scala.
  • Strong experience with software engineering principles, data structures, algorithms, and distributed systems.
  • Extensive experience with AWS Cloud.
  • Experience deploying applications across public cloud and enterprise cloud platforms.
  • Hands-on experience with Docker and Kubernetes.
  • Strong experience with MLOps tools including MLflow, Kubeflow, SageMaker, or Vertex AI.
  • Experience implementing CI/CD pipelines for machine learning applications.
  • Experience designing scalable ML infrastructure and distributed data processing systems.
  • Proven ability to lead technical initiatives and mentor engineering teams.
Preferred Qualifications
  • Experience building and deploying Large Language Model (LLM) solutions.
  • Hands-on experience with Amazon Bedrock.
  • Experience with Generative AI applications.
  • Strong understanding of TensorFlow, PyTorch, or Scikit-learn.
  • Experience with Deep Learning, NLP, or Computer Vision.
  • Experience with distributed model training and high-throughput inference systems.
  • Knowledge of model optimization and AI performance tuning.

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