Job Details

Skills

python
llm
docker
AWS

Summary

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.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 90967474
Position Id: 9035071
Posted 5 hours ago

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ML Engineer

Skills

Summary

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

Job Summary

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Required Qualifications

Preferred Qualifications

Dice Job Match Score™

Shivani Yaday

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