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Added 11 mins ago
ML
AI Engineer
MACHINE LEARNING TECHNOLOGIES LLC
Toronto, ON
- Full-time
Knowledge of financial markets and enterprise data systems.
Added 11 mins ago
W
Data Engineer
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- Full-time
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- Full-time
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Senior Data Platform Engineer
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Union Assistant Shift Engineer
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Added 2 hours ago
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Cloud Platform Engineer
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Toronto, ON
- $165,000 to $330,000 USD / year
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As a Cloud Platform Engineer, you'll envision and build robust systems and processes that ensure our infrastructure is scalable, reliable, and efficient. This can range from automating…
Added 2 hours ago
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Added 2 hours ago
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Baseten

Software Engineer - Voice AI (Inference Runtime)

Toronto, ON, Canada

$165,000 to $330,000 USD / year · Full-time

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Job details

Pay: $165,000 to $330,000 USD / year
Job type: Full-time
Apply by: Nov 28, 2026
Posting language: English
Posted: Oct 30, 2026

Original job description

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:
- Baseten leads Coval’s voice AI benchmark
- How Notion achieved 2-3x lower latency with AI Meeting Notes
- Cost-efficient, high-performance TTS with Qwen3-TTS
- Fine-tuning Qwen3-TTS for high-quality voice cloning
- The fastest Whisper - with streaming and diarization
- NVIDIA Nemotron 3 Diarization: real-time speaker labels at a cent per audio hour

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).

Compensation Range: $165K - $330K

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More about this job

Responsibilities

Own Voice AI product areas end to end, including architecture, implementation, rollout, and ongoing production operations. Build and operate high-performance real-time serving infrastructure for speech-to-text, text-to-speech, and voice-agent workloads, while coordinating delivery across teams and mentoring colleagues.

Requirements

Requires a bachelor's degree or higher in computer science or a related field, experience owning production-grade real-time, large-scale systems where p99 latency matters, and proficiency in at least one popular programming or scripting language. Candidates should have strong collaboration and communication skills, product judgment for developer tools, interest in ML infrastructure, and comfort using AI coding assistants; Python is a plus.

Skills

Real-Time Systems
Large-Scale Systems
Low-Latency System Design
Model Serving
Inference Runtime Optimization
Python
Voice AI
Speech-to-Text
Text-to-Speech
Streaming Infrastructure
GPU Performance Optimization
Dynamic Batching
Asynchronous Scheduling
Docker
Kubernetes
Technical Leadership

Benefits

Equity
Medical Insurance
Dental Insurance
Vision Insurance
Flexible Paid Time Off
Company-Wide Winter Break
Paid Parental Leave
Fertility and Family-Building Stipend
401(k)

Visa sponsorship

Not detected in the job text

Keywords

Voice AI
Inference Runtime
Model Serving
Real-Time Infrastructure
Speech-to-Text
Text-to-Speech
Voice Agents
Streaming I/O
Tail Latency
P99 Latency
Throughput Optimization
GPU Efficiency
Dynamic Batching
Asynchronous Scheduling
Python
Docker
Kubernetes
Service Meshes
Distributed Scheduling
vLLM
TensorRT
ONNX
PyTorch Profiler
Model Performance Profiling
AI Coding Assistants
Developer Platforms
SDKs
CLIs
APIs
Machine Learning Infrastructure

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