BaseTen Inc. logo

Software Engineer - Voice Agent

Job Overview

Location

San Francisco

Job Type

Full-time

Category

Software Engineering

Date Posted

April 27, 2026

Full Job Description

📋 Description

  • As a Software Engineer - Voice Agent at BaseTen Inc., you will be the primary owner of the company's in-house inference stack for Voice AI, playing a critical role in enabling mission-critical AI applications for industry-leading customers.
  • Day to day, you will own and lead Voice AI product areas end-to-end — from architecture and system design through implementation, rollout, and long-term production operations — while designing, building, and operating real-time, large-scale, high-performance model serving systems for STT, TTS, and voice agent workloads with clear SLOs.
  • You will join a small founding team focused on bringing state-of-the-art open source models into production for Voice AI customers across productivity, customer service, clinical conversation, creator tools, education, and more, collaborating closely with Forward Deployed Engineers, Model Performance Engineers, and sister engineering teams.
  • In this role, you will have the opportunity to push the boundaries of Voice AI, mentor teammates through code reviews and design docs, and gain deep expertise in ML/AI infrastructure while contributing to products used by companies like Cursor, Notion, and OpenEvidence.

Skills & Technologies

Python
Docker
Kubernetes
PyTorch
Apache Spark
Onsite
Degree Required

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BaseTen Inc.
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About BaseTen Inc.

BaseTen provides a serverless, GPU-accelerated platform that lets machine-learning teams deploy, scale and monitor custom models behind autoscaling inference endpoints. The service abstracts infrastructure management, supports PyTorch, TensorFlow and Hugging Face artifacts, and offers built-in observability, A/B testing and fine-tuning. Customers integrate via REST or GraphQL APIs and pay only for compute used. Founded in 2019 and headquartered in San Francisco, BaseTen targets data scientists and product teams seeking production-grade ML serving without Kubernetes complexity.

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