Software Engineer - Voice AI (Inference Runtime)

Baseten·San Francisco·23 апр.

Software Engineer - Voice AI (Inference Runtime)

🏢 ОфисMiddleПолная занятость

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Наша компания

Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products.

О роли

Voice is becoming the internet’s next interface, but a production-grade Voice AI system is "hard to build" You’ll join a small founding team of Baseten Voice AI, 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. You’ll make a meaningful impact on people’s daily lives and help reshape these industries

Чем предстоит заниматься

This is a high-impact, high-ownership role. You will be the primary owner of Baseten Voice AI - our in-house inference stack to power Voice AI models - from product roadmap through engineering implementation. You’ll partner closely with Forward Deployed Engineers, Model Performance Engineers, and sister engineering teams to push the boundaries of Voice AI

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 STT, TTS, 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 docs, and technical leadership

Develop world-class model serving stack for state-of-the-art open-source voice models - reduce end-to-end and tail latency (p95/p99), increase throughput, and improve GPU efficiency via profiling, runtime tuning, and server-level optimizations

Build large-scale, real-time infrastructure for multi-model voice agents - orchestrate STT, TTS, and agent components with streaming I/O to meet customer SLOs

Design tight training and inference iteration loops for voice model customization - enable fast evaluation, safe rollout, and rapid experimentation for custom voice model development

Past projects

The world's fastest Whisper — with streaming and diarization

Canopy Labs selects Baseten for Orpheus TTS inference

Наши требования

Bachelor's degree or higher in Computer Science or related field

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 taste in product, particularly developer-oriented tools

Interest in ML/AI infrastructure and willingness to learn

Strong collaboration and communication skills

Comfortable using AI coding assistants (e.g., Claude Code, Codex, Cursor) as a daily productivity multiplier — as an AI-native company, we see this as a must-have skill

Experience implementing pipeline-level model runtime optimizations such as dynamic batching, async scheduling, or decode-side throughput improvements

Experience building developer platforms: SDKs, CLIs, APIs, and self-serve workflows for ML or infrastructure products

Experience with containerization and orchestration technologies (Docker, Kubernetes), service meshes, or distributed scheduling

Familiarity with speech/audio ML models (STT, TTS, speech-to-speech)

Familiarity with model-serving runtimes (vLLM, TensorRT, ONNX)

Familiarity with systems-level performance profiling across host-device boundaries (e.g. PyTorch Profiler), diagnosing GPU utilization issues

Exposure to customer-facing engineering: pre-sales prototyping, technical discovery, or working directly with customers to ship solutions

Мы предлагаем

Competitive compensation, including meaningful equity

100% coverage of medical, dental, and vision insurance for employee and dependents

Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)

Paid parental leave

Fertility and family-building stipend through Carrot

Company-facilitated 401(k)

Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities

Baseten

San Francisco

ГрейдMiddle

ЗанятостьПолная занятость

РегионСША

ФорматОфис

ИсточникСкрыто

Опубликовано23 апр.

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