below marketmost similar roles pay hereabove market
This listing doesn't post a salary. Most similar roles pay
$169,550–$225,500.
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
1226 open roles
on FindRole.
Listed pay typically runs
$156,750–$215,000
across 5 roles with salary data.
SR Principal Software Engineer - LLM Engineering
As a SR Principal Software Engineer - LLM Engineering within the Commercial & Investment Bank Trust & Safety Fraud Prevention team, you will provide deep engineering expertise to build and deliver trusted technology products. You will lead the strategy, architecture, and development of model serving solutions for LLMs and GNNs across cloud and on-premises environments. Your daily work involves defining MLOps and LLMOps strategies, optimizing model inferencing for high throughput and low latency, and creating reusable software frameworks. You will utilize Python, PyTorch, TensorFlow, Hugging Face Transformers, Triton Inference Server, and vLLM. Key responsibilities include productionizing models on AWS using SageMaker, Bedrock, and EKS, while implementing agentic AI-enabled engineering patterns and infrastructure-as-code using Docker, Kubernetes, and Terraform to solve complex fraud prevention challenges.
What does a Software Engineer earn in California?
Median $214500 from 1193 postings across 76 companies.
Lead the strategy and architecture for model serving solutions for LLMs and GNNs across cloud and on-premises environments.
Define and implement MLOps and LLMOps strategies for end-to-end model lifecycle management, including training, deployment, and governance.
Optimize model inferencing for high throughput and low latency using quantization, model parallelism, and hardware acceleration.
Establish operating standards for agentic AI-enabled engineering to improve delivery speed, reliability, and code quality across the portfolio.
Create durable, reusable software and platform frameworks to standardize ML Engineering services across teams and functions.
Partner with data science and SRE teams to productionize models on AWS with a focus on observability and cost efficiency.
Oversee production operations for AI workloads, including monitoring, incident response, security, and compliance.
Translate complex technical concepts into actionable strategies to influence senior stakeholders and prioritize AI/ML capabilities.
What we're looking for
Formal training or certification on software engineering concepts and 10+ years of applied experience.
8+ years of AI/ML engineering experience with significant expertise in LLMs, GNNs, and other model architectures.
Demonstrated success architecting and deploying LLM and GNN solutions on AWS at enterprise scale.
Hands-on experience building LLM inference engines using Triton Inference Server and vLLM.
Advanced proficiency in Python and optimization techniques applied to deep learning frameworks like PyTorch, TensorFlow, and Hugging Face Transformers.
Deep understanding of LLMOps/MLOps with a track record of implementing best practices at scale.
Demonstrated experience designing and scaling agentic AI-enabled development patterns and establishing governance for secure handling of sensitive inputs.
Master’s or PhD in Computer Science, Engineering, or a related field (preferred).
Video Coding
AV1
AV2
AVC
HEVC
VVC
Deep Learning
Computer Vision
C++
Python
gStreamer
Docker
REST APIs
XML
JSON
Git
GitHub
ABR Algorithms
Video Processing