Software Engineer - Voice AI (Inference Runtime)
Baseten is hiring a Software Engineer - Voice AI (Inference Runtime) for a remote role open to applicants in United States. It pays $165k-$330k a year and Level rates it ; you can apply on Baseten.
Level's read on this job
- Builds AI ●●●● is how Level rates this software engineer role: the job is building AI systems.
- Pay on this posting starts in line with the typical software engineer posting on Level.
- This is listed as a remote role.
- The posting mentions Claude, vLLM and PyTorch among its tools and skills.
- Baseten has 105 other open roles on Level.
AI in this role
Build and lead real-time inference infrastructure and runtime stacks for production-grade Voice AI models.
ABOUT BASETEN
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 ship AI products.
THE ROLE
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.
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.
EXAMPLE INITIATIVES
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:
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 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.
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 — as an AI-native company, we see this as a must-have skill.
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
(U.S. only) 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
(U.S. only) Company-facilitated 401(k)
Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.
Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.
At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.
We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).
How we rate this
Software Engineer - Voice AI (Inference Runtime) at Baseten rates 95 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Pay
- This job starts at
- $165k
- Typical software engineer job
- $168k
This posting starts close to the typical software engineer job. See software engineer jobs
Questions you could be asked
- Walk me through fine-tuning a model: what data did you use, and how did you check the result?
- What have you built with speech recognition or text-to-speech, and where did it break?
- Tell me about a research question you investigated. What did you find?
- Tell me about a project where inference runtime was part of your work. What did you do?
- Tell me about a project where voice ai was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Fine-tuning, Speech, AI Research, Inference Runtime, and Voice AI. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.
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