Design customer solutions through API and data integration, AI and third-party connections, and alignment with product and development teams. Full remote work is available.
About this role
This software engineering role sits within the platform and ML services area of a voice-centered multimodal AI product. The team designs systems that apply machine learning to communication data and supports deployment at large scale, including more than one million analysis requests per day.
The engineer designs and implements distributed-system architectures, cloud-native infrastructure, MLOps pipelines, and real-time data processing and analytics platforms. Named technologies include AWS, Kubernetes on EKS, Python, KEDA, Karpenter, KServe, GitHub Actions, Argo CD, SQS, SNS, MemoryDB, DynamoDB, and Kinesis Streams. The role also covers reliability, scalability, latency, cost optimization, performance tuning, and collaboration with research and development teams on prototypes and productization.
Applicants must have at least three years of distributed-systems development experience on a cloud platform, particularly AWS; deep practical knowledge of container orchestration such as Kubernetes; experience designing and implementing CI/CD pipelines; advanced Python or equivalent programming ability; and experience with cost optimization and performance tuning.
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