Senior Associate Applied AI ML

JPMorgan Chase

Confirmed live yesterday High trust

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Work type
On-site
Location
New York, NY
Posted
155 days ago
Freshness
Confirmed live yesterday

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Salary context

How this pay compares to similar roles

Similar $212k
$158k most similar roles pay here $274k

This listing doesn't post a salary. Most similar roles pay $169,387–$254,750.

Based on 240 similar postings.

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About JPMorgan Chase

JPMorgan Chase & Co. is a global financial services firm and one of the largest banks in the world, offering investment banking, commercial banking, asset management, and consumer financial services.

JPMorgan Chase currently has 1117 open roles on FindRole.

Listed pay typically runs $186,160–$215,000 across 7 roles with salary data.

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At a glance

TL;DR · Senior Associate Applied AI ML

As an Applied AI ML-Senior Associate within the AI for Operations organization, you will design, build, and scale cutting-edge Natural Language Processing solutions to improve experiences for customers and internal agents. You will manage the end-to-end model lifecycle by partnering with product, engineering, operations, and risk stakeholders to translate operational needs into production-grade capabilities like intelligent search, summarization, classification, and next-best-action recommendations. Your daily work involves analyzing complex datasets, developing models and algorithms, ensuring code efficiency, and mitigating risks associated with machine learning systems. You will utilize expertise in machine learning, Graph learning, recommendation systems, network analysis, NLP, Reinforcement learning, MLOps, Gen AI, and LLMs. The role requires a strong grasp of core computer science concepts, data structures, algorithms, and experience managing large structured and unstructured datasets within cloud environments like AWS, GCP, or Azure.

What you'll do

  • Design, build, and scale production-grade NLP solutions like intelligent search, summarization, and classification.
  • Apply technical judgment to select appropriate models, including modern LLM-based methods.
  • Evaluate model performance using rigorous metrics to ensure reliability, security, and scalability.
  • Improve data quality and establish feedback loops for monitoring models in production.
  • Translate operational needs from stakeholders into actionable machine learning capabilities.
  • Analyze complex datasets to inform decisions on real-world applications and system improvements.
  • Identify and mitigate risks associated with machine learning and prediction systems.
  • Develop and implement algorithms to enhance existing products and internal workflows.

What we're looking for

  • Master's degree in Computer Science, Machine Learning, or a related field with 3+ years of experience.
  • Ph.D. in Computer Science, Machine Learning, or a related field with 1+ year of experience.
  • Expertise in machine learning, Graph learning, recommendation systems, network analysis, NLP, Reinforcement learning, MLOps, Gen AI, or LLMs.
  • Solid understanding of core computer science concepts, including common data structures and algorithms.
  • Experience conducting design and code reviews.
  • Proficiency in cloud environments such as AWS, GCP, or Azure.
  • Experience managing and deriving insights from large structured and unstructured datasets.

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