Software Engineer - Voice AI (Inference Runtime)
Build and own high-performance inference runtime for Voice AI models including STT, TTS, and voice agents. Design real-time systems with low tail latency, collaborate cross-team, and optimize model serving for production workloads. Requires CS degree and real-time systems experience.
About the job
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 STT, TTS, and voice agent workloads with clear SLOs for mission-critical customer deployments.
- Drive cross-team collaboration with sister engineering teams to solve full-stack technical problems, aligning on priorities, and coordinating end-to-end delivery across the product surface area.
- Mentor teammates through code reviews, design docs, and technical leadership.
Requirements
- 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
Nice to Have
- 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.
Benefits
- 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
- Paid parental leave
- Fertility and family-building stipend through Carrot
- Company-facilitated 401(k)
- Exposure to a variety of ML startups
Skills
Python, Kubernetes, Docker, PyTorch, vLLM, TensorRT, Onnx, Whisper, Stt, Tts
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