Software Engineer III - LLM Developer

Overview

We have an exciting and rewarding opportunity for you to take your software engineering career to the next level.

As a Software Engineer III at JPMorgan Chase within the Consumer and community banking technology team, you serve as a seasoned member of an agile team to design and deliver trusted market-leading technology products in a secure, stable, and scalable way. You are responsible for carrying out critical technology solutions across multiple technical areas within various business functions in support of the firm’s business objectives.

Job Responsibilities

• Oversee setting direction, development, and implementation of ML and GenAI driven solutions
• Develop codes and automations to provision and manage cloud infrastructure and services required for model serving and inferencing.
• Create pipelines for model and pipeline deployment and execute them for CI/CD process.
• Deploy and manage Machine Learning platform and platform features in production.
• Be responsible for stability, reliability, security and production run books of the machine learning solution in production.
• Be responsible for registering the models artifacts, maintaining code coverage, implementing functional and non-functional tests in the pipeline and maintaining CI/CD frameworks.
• Collaborate with Machine Learning engineers, product managers, key business stakeholders, engineering, and platform partners to deploy projects that deliver cutting-edge machine learning-driven digital solutions.
• Communicate and collaborate with Platform and Engineering partners to bring in the latest advancements in order to improve the scale, consistency, reliability and trustworthiness of the ML solutions
  
  

• Formal training or certification on software engineering concepts and 3+ years applied experience.
• Proven experience in deploying AI/ML applications in a production environment, with skills in deploying models on AWS platforms such as SageMaker or Bedrock.
• Proven experience with MLOps practices, encompassing the full cycle from design, experimentation, deployment, to monitoring and maintenance of machine learning models.
• Demonstrated expertise in deploying solutions involving machine learning frameworks: Tensorflow, Pytorch, pyG, Keras and Scikit-Learn.
• Expert skill in system monitoring tools like Apica, Dynatrace, Grafana etc.
• Expert skill in CI/CD tools like Jenkins, Spinnaker, Git, Bitbucket etc.
• Expert in Infrastructure as a code frameworks i.e. Terraform, EaC (Environment as Code)
• Proficiency in programming languages such as Python or Java etc.
• Expert knowledge of one of the cloud computing platforms : Amazon Web Services (AWS), containerization technologies (Docker, Kubernetes, Amazon EKS, ECS)
• Working proficiency in one of the end to end Machine Learning framework or tool i.e. MLFlow, Kubeflow, sagemaker studio, Databricks etc
  
  

• Good understanding of AI/ML algorithms and techniques, including deep learning, reinforcement learning, and natural language processing (NLP).
• Experience with Kubernetes based platform for Training or Inferencing.
• Experience of building and managing large scale feature stores.
• Proficiency in writing comprehensive test cases, with a strong emphasis on using testing frameworks such as pytest to ensure code quality and reliability.
• Understanding of finance or investment banking businesses is an added advantage.