Applied AI ML Lead

JPMorgan Chase

Closes in 4 days

Quick summary

Work type
On-site
Location
Columbus, OH
Posted
18 days ago
Closes
Jul 2, 2026 (soon)
Nearby
99+ roles within 25 mi

Market check

Salary context

How this pay compares to similar roles

Similar $213k
$164k most similar roles pay here $255k

This listing doesn't post a salary. Most similar roles pay $179,337–$246,150.

Based on 240 similar postings.

Employer

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 394 open roles on FindRole.

Listed pay typically runs $152,000–$215,000 across 207 roles with salary data.

Most-posted roles

View all roles at JPMorgan Chase

At a glance

TL;DR · Applied AI ML Lead

Role Posting Log in to save

As a Senior Machine Learning Engineer on the AI Solutions team at Chase, you will lead cutting-edge initiatives to enhance virtual assistant capabilities by leveraging advanced NLP and deep learning techniques. Your day-to-day responsibilities include optimizing small language models (SLMs) for financial applications, conducting experiments with large language models (LLMs), and driving production deployment of machine learning solutions. You will utilize Python, neural networks like Transformers, and open-source embedding models to build scalable ML pipelines and automate workflows. Additionally, you will apply tokenization, named entity recognition, and semantic search techniques to improve user interaction on the chase.com website. With expertise in distributed training, model fine-tuning, and performance optimization, you will contribute to monthly releases and ensure continuous improvement of AI solutions for transaction search applications.

Skills

Python Supervised Learning Unsupervised Learning Feature Engineering Hyperparameter Optimization Neural Networks Convolutional Neural Networks Recurrent Neural Networks Long Short-Term Memory Transformers Open Source Embedding Models Tokenization Named Entity Recognition Semantic Search Topic Modeling Prompt Engineering System Prompt Design Retrieval-Augmented Generation RAG Instruction Fine-Tuning Parameter-Efficient Fine-Tuning Multi-adapter Architectures Domain Adaptation Synthetic Data Generation Dense Retrieval Sparse Retrieval Hybrid Search Embedding-based Semantic Search Precision Recall F1 Score Mean Reciprocal Rank MRR Normalized Discounted Cumulative Gain NDCG SQUAD Metrics Exact Match Perplexity Multi-class Evaluation Multi-label Evaluation Latency Profiling Human-in-the-loop Evaluation Distributed Training Data Parallel Fully Sharded Data Parallel Mixed Precision Training Multi-GPU Scaling KV Caching Semantic Caching Distributed Inference Quantization Low-latency API Design Snowflake Databricks Sagemaker

What you'll do

  • Lead the development of scalable AI solutions using large and small language models.
  • Optimize small language models for efficiency in finance domain applications.
  • Design and execute experiments to enhance performance on targeted tasks.
  • Conduct thorough analysis of business needs using state-of-the-art research.
  • Own machine learning solution for transaction search application, including optimization.

What we're looking for

  • Bachelor's degree in Computer Science or related field plus 7 years of experience in AI/ML roles.
  • Master’s degree in Computer Engineering or related field plus 5 years of experience in data sciences and ML.
  • Experience implementing scalable machine learning pipelines using Python.
  • Proficiency in neural networks, including CNNs, RNNs, LSTMs, and Transformers for model fine-tuning.
  • Expertise in tokenization, named entity recognition, semantic search, and topic modeling to analyze text data.
  • Utilize precision, recall, F1 scores, and other metrics to assess ML model performance effectively.
  • Experience with distributed training techniques and optimization strategies for small language models.

Related searches

More Applied AI ML Lead [Multiple Positions Available] jobs Applied AI ML Lead [Multiple Positions Available] jobs in Columbus All jobs at JPMorgan Chase

More like this

Similar roles

Applied AI ML Lead

JPMorgan Chase

Palo Alto, CA 10 days ago $185,900–$260,000
Python SQL PySpark Apache Spark Scikit-Learn TensorFlow PyTorch Keras Jupyter Lab Tableau Shapley Analysis Shell scripting Bash scripting GitHub Bitbucket NLP TF-IDF ARIMA SARIMA Regression techniques Classification methods Ensemble Methods Clustering Dimensionality Reduction Logistic Regression Decision Tree Random Forest Support Vector Machine Naive Bayes K-Nearest Neighbors Neural Network RNN LSTM CNN
Save

Applied AI ML Lead

JPMorgan Chase

Jersey City, NJ 5 days ago $164,350–$260,000
Python PyTorch CI/CD Kubernetes AWS Docker Git PostgreSQL Responsible AI Semantic Modeling Transformer Architectures GPU Development Agentic AI Systems Version Control Code Review Testing MLOps
Save

AI/ML Lead Engineer

Franklin Templeton

Stamford, Connecticut +2 12 days ago $180,000–$212,000
Python LangChain OpenAI Docker Kubernetes AWS Azure GCP Pinecone FAISS RAG Prometheus CI/CD GraphQL PostgreSQL Redis Terraform GitLab Jenkins
Hybrid
Save

AI/ML Enablement Lead Engineer, Solutions

US Bank

Chicago, IL +4 4 days ago $139,230–$163,800
Python Azure AWS Kubernetes LLMs RAG API-based architecture microservices architecture CI/CD Terraform PostgreSQL Snowflake Git Jira Confluence Docker Prometheus Grafana
Hybrid
Save

Lead Director, AI/ML Engineering

CVS Health

Remote (Woonsocket, RI) +4 9 days ago $144,200–$288,400
Claude Skills Framework MCP Azure GCP AWS CI/CD Kubernetes Docker Python Snowflake BigQuery Terraform Prometheus Grafana DataOps Scrum LLM HIPAA CVS Health's Squad model
Remote
Save