Software Engineer III – AI Platform Space Engineer
| Company | JP Morgan Chase |
|---|---|
| Location | San Francisco, CA, USA |
| Salary | $Not Provided – $Not Provided |
| Type | Full-Time |
| Degrees | |
| Experience Level | Mid Level |
Requirements
- Formal training or certification on software engineering concepts and 3+ years applied experience.
- Good knowledge of cloud computing delivery models (IaaS, PaaS, and SaaS) and deployment models related to Public, Private and Hybrid Cloud services
- Strong hands-on coding experience with python and/or Golang
- Proficient in Linux/Environments, including scripting and administration.
- Hands on experience in solutions design and engineering, experience with containerization (Docker, Kubernetes) and cloud service providers (AWS, Azure, GCP). Experience with Infrastructure as code (Terraform, CloudFormation) and automation tools (Ansible, Chef, Puppet).
- Experience in developing, debugging, and maintaining code in a large corporate environment with one or more modern programming languages and database querying languages
- Overall knowledge of the whole Software Development Life Cycle
- Solid understanding of agile methodologies such as CI/CD, Application Resiliency, and Security
- Demonstrate knowledge of software applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.)
Responsibilities
- Develops and engineers infrastructure platforms that are secure, scalable, and optimized for AI and machine learning workloads.
- Collaborates with AI teams to understand computational needs and translate these into infrastructure requirements.
- Monitors, manages, and optimizes cloud resources to maximize performance and minimize costs.
- Designs and implements continuous integration and delivery pipelines for machine learning workloads.
- Develops automation scripts and infrastructure as code to streamline deployment and management tasks.
- Creates secure and high-quality code using the syntax of at least one programming language with limited guidance
- Designs, develops, codes, and troubleshoots with consideration of upstream and downstream systems and technical implications
- Applies technical troubleshooting to break down solutions and solve technical problems of basic complexity
- Gathers, analyzes, synthesizes, and develops visualizations and reporting from large, diverse data sets in service of continuous improvement of software applications and systems
- Contributes to software engineering communities of practice and events that explore new and emerging technologies.
- Adds to team culture of diversity, equity, inclusion, and respect
Preferred Qualifications
- Experience in one or more High Performance Computing and Machine Learning frameworks such as vLLM, Ray.io, Slurm is preferable.
- Familiarity with cloud data services and big data processing tools.
- Foundational understanding of Machine learning concepts such as transformer architecture, ML training and inference
- Strong background in network architecture, database programming (SQL/NoSQL), and data modeling.
- Deep understanding of cloud component architecture: Microservices, Containers, IaaS, Storage, Security, Knowledge of routing/switching technologies.