Expoint - all jobs in one place

The point where experts and best companies meet

Limitless High-tech career opportunities - Expoint

JPMorgan Senior Lead Software Engineer - LLMs 
United States, Delaware, Wilmington 
215563671

Yesterday

Job responsibilities

  • Develops cutting edge AI/ML Platform solutions using LLMs, public cloud and modern standards and patterns.
  • Develops and implements state-of-the-art generative AI services leveraging Azure Open AI models and AWS Bedrock service.
  • Develops solutions using AWS Cloud Services for compute, storage, databases, and security and Azure Services
  • Develops advanced monitoring and management tools for high reliability and scalability.
  • Architect and implement distributed ML infrastructure, including inference, training, scheduling, orchestration, and storage.
  • Optimizes system performance by identifying and resolving inefficiencies and bottlenecks.
  • Works closely with the Product team to design, build and deliver capabilities in agile sprints.
  • Collaborates with cross-functional teams, including data scientists, software engineers, and designers, to integrate generative AI into various applications and products.

Required qualifications, capabilities, and skills

  • Formal training or certification on software engineering concepts and 5+ years applied experience.
  • Strong coding skills and experience in developing large-scale ML systems.
  • Deep expertise in AWS / GCP and Kubernetes ecosystem, including EKS, Helm, and custom operators.
  • Hands-on experience with ML frameworks (TensorFlow, PyTorch, JAX, scikit-learn).
  • Hands-on experience working on AWS Cloud Based applications development using EC2, EKS, Lambda, SQS, SNS, RDS Aurora MySQL & Postgres, DynamoDB, and Kinesis.
  • Deep expertise across application, data, security, and infrastructure disciplines
  • Experience in setting up public cloud infrastructure using TerraForm.
  • Experience working containerized services on Kubernetes or ECS
  • Experience with Python, Java, and REST APIs.
  • Solid understanding of improving and debugging backend performance bottlenecks.
  • Experience with application production readiness, production monitoring, and production issue triaging

Preferred qualifications, capabilities, and skills

  • Knowledge of AWS Sagemaker and data analytics tools will be a plus.
  • Knowledge on new model architectures using optimizations like quantization and pruning.
  • Ability to adapt to new technologies and learn quickly in a fast-paced environment
  • Knowledge or experience with working on Azure