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Remote 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 ...

Wolters Kluwer

Senior Legal Counsel

Columbus, OH

$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 remote large language model llm jobs pay per hour?

As of Jul 30, 2026, the average hourly pay for remote 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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Remote Large Language Model Llm jobs near you
A map of the United States highlighting the number of Remote Large Language Model Llm job openings by state according to ZipRecruiter. The image is accompanied by a detailed chart listing the number of Remote 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 6 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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