Inflection AI

2 months ago

Research Engineer, Voice

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 4 hours agoStatus: Live

Job Summary

Research, develop, and deploy voice and audio neural models (speech synthesis, recognition, audio generation, and spoken dialogue) for Pi. Build production-grade training and inference pipelines with low latency, collaborate with ML engineers and product teams, and push forward neural audio codecs, diffusion-based synthesis, and multimodal models to deliver natural, expressive voice experiences at scale.

Location: Palo Alto

Workplace: Onsite

Employment Type: Full time

Job Function: Research & Scientific (R&D)

Key Responsibilities

•Research, develop, and optimize neural models for voice and audio—including text-to-speech, automatic speech recognition, audio generation, and spoken dialogue systems.
•Build and maintain production-grade training and inference pipelines for voice models, with close attention to latency, naturalness, and scalability.
•Run experiments end-to-end: data curation, model architecture design, training, evaluation, and ablation studies.
•Collaborate with ML engineers, product teams, and infrastructure to integrate voice models into Pi’s real-time conversational stack.
•Explore and apply advances in neural audio codecs, diffusion-based synthesis, streaming architectures, and multimodal foundation models to improve Pi’s voice experience.

Pay and Benefits

Salary: USD 225,000 - 325,000 annually

Equity and Bonus:Equity

Perks:Health Insurance401kPaid LeaveParental LeaveVisa Assistance

Key Requirements

•2-5 years of research or engineering experience (including graduate work) in audio, speech, or multimodal ML.
•Strong proficiency in PyTorch and hands-on experience training and debugging large-scale neural models on GPU/accelerator clusters.
•Solid understanding of audio and speech fundamentals (spectrograms, mel features, vocoders, codec-based representations, and signal processing).
•Ability to take a research idea from prototype to production: reading papers and writing CUDA-aware training loops.
•Familiarity with modern generative architectures for audio (diffusion models, autoregressive codecs, flow-matching) and their trade-offs.

Experience:2-5 yearsAudioSpeechMultimodal ML

Education:Bachelor's

Skills:CommunicationProblem-solving

Languages:English

Tech Stack:PyTorchCUDAGPUDiffusion modelsText-to-speechSpeech recognitionNeural networks

Company Brief

Inflection AI

Develops conversational AI and personal-assistant technologies, including the Pi chatbot, to enable more natural human–computer interaction and simplify access to information and productivity tools.

Industry: AI & Machine Learning

Company Size: Medium (51 to 250 employees)

Growth: Early Stage Startup

Headquarters: Palo Alto, United States

Founded: 2022

Website LinkedIn

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Inflection AI

2 months ago

Research Engineer, Voice

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 4 hours agoStatus: Live

Job Summary

Location: Palo Alto

Workplace: Onsite

Employment Type: Full time

Job Function: Research & Scientific (R&D)

Key Responsibilities

•Research, develop, and optimize neural models for voice and audio—including text-to-speech, automatic speech recognition, audio generation, and spoken dialogue systems.
•Build and maintain production-grade training and inference pipelines for voice models, with close attention to latency, naturalness, and scalability.
•Run experiments end-to-end: data curation, model architecture design, training, evaluation, and ablation studies.
•Collaborate with ML engineers, product teams, and infrastructure to integrate voice models into Pi’s real-time conversational stack.
•Explore and apply advances in neural audio codecs, diffusion-based synthesis, streaming architectures, and multimodal foundation models to improve Pi’s voice experience.

Pay and Benefits

Salary: USD 225,000 - 325,000 annually

Equity and Bonus:Equity

Perks:Health Insurance401kPaid LeaveParental LeaveVisa Assistance

Key Requirements

•2-5 years of research or engineering experience (including graduate work) in audio, speech, or multimodal ML.
•Strong proficiency in PyTorch and hands-on experience training and debugging large-scale neural models on GPU/accelerator clusters.
•Solid understanding of audio and speech fundamentals (spectrograms, mel features, vocoders, codec-based representations, and signal processing).
•Ability to take a research idea from prototype to production: reading papers and writing CUDA-aware training loops.
•Familiarity with modern generative architectures for audio (diffusion models, autoregressive codecs, flow-matching) and their trade-offs.

Experience:2-5 yearsAudioSpeechMultimodal ML

Education:Bachelor's

Skills:CommunicationProblem-solving

Languages:English

Tech Stack:PyTorchCUDAGPUDiffusion modelsText-to-speechSpeech recognitionNeural networks

Company Brief

Inflection AI

Industry: AI & Machine Learning

Company Size: Medium (51 to 250 employees)

Growth: Early Stage Startup

Headquarters: Palo Alto, United States

Founded: 2022

Website LinkedIn