Top Tech Jobs & Startup Jobs in Charlotte, NC

As a Customer Success Engineer, you'll drive adoption and satisfaction for enterprise customers using Deepgram's voice AI technology, fostering strong relationships and aligning technical solutions with business objectives.

As a Billing & Analytics Software Engineer, you'll design and maintain the billing pipeline, integrate billing systems, and develop customer-facing analytics dashboards to support revenue recognition and operational observability.

The Account Executive at Deepgram is responsible for building a sales pipeline, exceeding targets, collaborating with teams, and understanding customer needs to sell the voice AI platform.

Lead the operational accounting function as Deepgram scales toward IPO, overseeing monthly close, ERP migration, and the development of accounting policies and controls.

As an ML Ops Infrastructure Engineer, you will design CI/CD pipelines for ML, maintain deployment systems, and implement monitoring while collaborating with research teams to ensure model quality and performance.

Lead the edge deployment strategy for Deepgram's speech AI models, optimizing for performance on constrained hardware and collaborating with partners like Qualcomm to deliver secure solutions for defense customers.

As a Network Engineer at Deepgram, you'll optimize global network infrastructure for real-time audio streaming, focusing on latency reduction across hybrid cloud and on-premises environments.

As a Systems Architect, you'll define and drive the infrastructure architecture for AI/ML workloads, design multi-cloud strategies, manage compute orchestration and storage systems, and lead capacity planning, while also collaborating with engineering leadership.

The role involves researching and developing large language models (LLMs) with a focus on transformer architecture, data curation, distributed training, and optimization. Responsibilities include conducting experiments, collaborating with teams, and staying updated on deep learning advancements.

The engineer will build and operate AI/ML infrastructure, managing services on AWS and bare metal, using tools like Kubernetes and Terraform.