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Baseten

Runs AI models for production software

Software Engineer - Voice AI, Inference Runtime

Applied Machine LearningConfirmed live in the last 24 hours
Full-time

About the Job

Requirements

  • A bachelor's degree or higher in Computer Science or a related field.
  • A proven track record owning production-grade real-time, large-scale systems where tail latency (p99) matters.
  • Proficient coding abilities in one or more popular programming or scripting languages; Python proficiency is a plus.
  • Good product judgment, particularly for developer-oriented tools.
  • Interest in machine learning or artificial intelligence infrastructure and willingness to learn.
  • Strong collaboration and communication skills.
  • Comfort using artificial-intelligence coding assistants such as Claude Code, Codex, or Cursor as a daily productivity tool.

Responsibilities

  • Own and lead Voice AI product areas end-to-end, from architecture and system design through implementation, rollout, and long-term production operations.
  • Design, build, and operate real-time, large-scale, high-performance model-serving systems for speech-to-text, text-to-speech, and voice-agent workloads for mission-critical customer deployments.
  • Drive cross-team collaboration with sister engineering teams to solve full-stack technical problems, align on priorities, and coordinate end-to-end delivery across the product surface area.
  • Mentor teammates through code reviews, design documents, and technical leadership.

Desired Qualifications

  • Experience implementing pipeline-level model-runtime optimizations such as dynamic batching, asynchronous scheduling, or decode-side throughput improvements.
  • Experience building developer platforms, including software development kits, command-line interfaces, application programming interfaces, and self-serve workflows for machine-learning or infrastructure products.
  • Experience with containerization and orchestration technologies such as Docker and Kubernetes, service meshes, or distributed scheduling.
  • Familiarity with speech and audio machine-learning models, including speech-to-text, text-to-speech, and speech-to-speech.
  • Familiarity with model-serving runtimes such as vLLM, TensorRT, and ONNX.
  • Familiarity with systems-level performance profiling across host-device boundaries, such as PyTorch Profiler, and diagnosing GPU-utilization issues.
  • Exposure to customer-facing engineering, including pre-sales prototyping, technical discovery, or working directly with customers to ship solutions.

About the Company

Baseten

Runs AI models for production software

Baseten runs AI models for software companies that need fast, reliable responses inside their products, from text generation to speech and image processing. Its Inference Stack combines optimized model runtimes with infrastructure that deploys, serves, and monitors custom or open models in production. Teams package models with its open source Truss tool, while Model APIs let developers test ready-to-use models and Training runs jobs that adapt models to their own data. Customers pay for computing time or tokens processed, with negotiated plans for larger deployments and support needs. Baseten was founded in 2019 and is headquartered in San Francisco.

Company size
201-500
Company stage
Series F
Total funding
$2.1B
Headquarters
San Francisco, CA
Founded
2019

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