Software Development Engineer II, AWS SageMaker AI

Description

At AWS Sage Maker AI, we’re making it easy to build state-of-the-art foundation models on the cloud. Model Factory is our platform for building, training, customizing, and evaluating foundation models tead of hand-chaining data prep, distributed training, evaluation, and deployment across thousands of GPU and AWS Trainium devices, Model Factory lets teams express the whole lifecycle as a single, contract-validated workflow — orchestrated, reproducible, and fully managed.

As LLMs and Generative AI scale, Model Factory is the platform that turns frontier training research into a reliable, repeatable pipeline for our internal teams and customers.

• Design, build, test, and operate services that orchestrate foundation-model data preparation, training, evaluation, and deployment as reliable, contract-validated workflows.
• Own delivery of individual components end-to-end — from design and implementation through deployment, monitoring, and on-call operations.
• Build and extend compute-backend integrations and job launchers — submitting, monitoring, and recovering large-scale training jobs across Sage Maker (Training/Processing/Hyper Pod), EMR, AWS Batch, and Kubernetes/EKS.
• Improve the platform’s resiliency and operability for long-running distributed jobs — checkpoint/resume, fault detection and recovery, retries, and observability (metrics, logging, experiment tracking).
• Contribute to the SDK, workflow orchestration, and schema/contract layer that teams use to declare and run jobs, and to the CDK infrastructure that deploys the platform.
• Integrate containerized training and evaluation frameworks (e.g., PyTorch/FSDP, verl, NeMo/Megatron) into the platform’s task and recipe model.
• Contribute to design and architecture discussions, write clear technical designs, and uphold engineering best practices (code review, testing, operational readiness).
• Collaborate with ML scientists and internal customers to translate training requirements into reliable, self‑service platform capabilities, and help onboard and mentor interns and new engineers as you grow.

• 3+ years of non-internship professional software development experience
• 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
• 1+ years of software development engineer or related occupational experience
• 1+ years of designing and developing large‑scale, multi-tiered, multi-threaded, embedded or distributed software applications, tools, systems, and services using: C#, C++, Java, or Perl experience
• 1+ years of Object Oriented Design experience
• Bachelor’s degree or foreign equivalent in Computer Science, Engineering, Mathematics, or a related field
• Experience programming with at least one software programming language

• 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
• Bachelor’s degree in computer science or equivalent
• Experience with workflow/pipeline orchestration (Airflow, Step Functions, or similar) and event-driven or service-oriented architectures.
• Experience with container and cluster compute (Kubernetes/EKS, Ray, Slurm, AWS Batch) and cloud infrastructure-as-code (AWS CDK/Cloud Formation).
• Experience building and operating fully‑managed cloud services at scale, including resiliency, checkpointing, and fault tolerance for long-running jobs.
• Familiarity with machine-learning / deep-learning training workflows, GPU/accelerator compute (Sage Maker Hyper Pod, AWS Trainium, P5-class GPUs), or distributed‑training frameworks (PyTorch FSDP, Megatron‑LM, Deep Speed, verl).

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