About this role
Senior Lead Software Engineer for JPMorgan Chase’s AI platform/infrastructure work, partnering with agile teams to build secure, scalable cloud platforms for AI and machine learning workloads. The role emphasizes production-quality code, cloud resource optimization, and CI/CD pipelines for machine learning.
Key Responsibilities
- Architect and deploy secure, scalable cloud infrastructure for AI/ML workloads
- Build and review secure production code and debug issues
- Design and implement CI/CD pipelines for machine learning workloads
- Develop automation scripts and Infrastructure as Code for streamlined deployments
- Monitor, manage, and optimize cloud resources for performance and cost
Technical Overview
The engineer will architect and deploy AI-optimized cloud infrastructure platforms using secure cloud components, containerization (Docker, Kubernetes), and Infrastructure as Code. They will implement CI/CD pipelines for machine learning workloads and build automation scripts while monitoring and optimizing performance and cost across AWS/Azure/GCP.
Ideal Candidate
The ideal candidate is a senior/lead software engineer with 5+ years of software engineering experience who has architected and deployed secure, scalable cloud infrastructure for AI and machine learning workloads. They are hands-on with Python, Docker, Kubernetes, Infrastructure as Code, and CI/CD pipelines, with foundational ML knowledge (transformer architecture, training, inference) across AWS, Azure, and GCP.
Must-Have Skills
5+ years of applied experience in software engineering conceptsProficiency in at least one programming languagesuch as PythonGoJavaor C#Strong knowledge of cloud computing delivery models (IaaSPaaSSaaS) and deployment models (PublicPrivateHybrid Cloud)Foundational understanding of machine learning conceptsincluding transformer architectureML trainingand inferenceExperience in solutions design and engineeringcontainerization (DockerKubernetes)and cloud service providers (AWSAzureGCP)Experience with Infrastructure as CodeDeep understanding of cloud component architecture: MicroservicesContainersIaaSStorageSecurityand routing/switching technologiesAbility to independently tackle design and functionality problems with minimal oversight
Nice-to-Have Skills
Foundational understanding of NVIDIA GPU infrastructure software (e.g.DCGMBCMTriton Inference)Hands-on experience with mac
Tools & Platforms
PythonGoJavaC#DockerKubernetesAmazon Web ServicesAWSAzureGoogle Cloud PlatformGCPInfrastructure as Codecontinuous integration and deliveryCI/CDNVIDIA GPU infrastructure softwareDCGMBCMTriton Inferencemac
Required Skills
system designsecure production codecode reviewdebuggingcloud infrastructureAI and machine learning workloadsPythontransformer architectureML traininginferenceDockerKubernetesAmazon Web ServicesAzureGoogle Cloud PlatformInfrastructure as Codemicroservicescontinuous integration and deliveryCI/CDautomation scriptsmonitoringcost efficiency
Hard Skills
system designapplication developmenttestingoperational stabilitysecure production codedebugging codecloud infrastructure platformsmachine learning workloadsmachine learning conceptstransformer architectureML traininginferencecontainerizationDockerKubernetesAmazon Web ServicesAWSAzureGoogle Cloud PlatformGCPInfrastructure as CodeInfrastructure as Code (IaC)microservicesstoragesecurityrouting/switching technologiescontinuous integration and delivery pipelinesCI/CD pipelinesautomation scriptsagile team workproduction code reviewmonitoring cloud resourcescost efficiency optimizationpublic cloudprivate cloudhybrid cloudIaaSPaaSSaaS
Soft Skills
technical guidance and directioncollaboration with technical teamscollaboration with contractorscollaboration with vendorsproblem-solvinginformed decision-makingdiversityequityinclusionand respect cultureability to work with minimal oversightleadership through influence
Keywords for Your Resume
Senior Lead Software EngineerAI Platform engineeragile teamtechnical guidancesecure production codecode reviewdebugproblem-solving methodologiesSoftware Development Life Cyclecloud infrastructure platformsAI and machine learning workloadsPythonGoJavaC#transformer architectureML traininginferenceDockerKubernetesAmazon Web ServicesAWSAzureGoogle Cloud PlatformGCPInfrastructure as CodeMicroservicesContainersIaaSPaaSSaaScontinuous integration and delivery pipelinesCI/CDautomation scriptsrouting/switching technologies
Deal Breakers
Must have 5+ years of applied experience in software engineering concepts, Must be proficient in at least one programming language (Python, Go, Java, or C#), Must have experience with containerization (Docker, Kubernetes) and cloud providers (AWS, Azure, GCP), Must have experience with Infrastructure as Code
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