About the Role

We’re looking for a Member of Technical Staff (MTS), Research Engineer focused on voice and audio to help advance the spoken intelligence behind Pi. In this role, you’ll work at the intersection of research and production—developing, training, and shipping neural models across the full spectrum of voice: speech synthesis, recognition, audio generation, and real-time spoken dialogue. You’ll collaborate closely with ML engineers, product teams, and infrastructure to turn cutting-edge ideas in areas like neural audio codecs, diffusion-based TTS, and multimodal foundation models into the natural, expressive voice experiences that millions of Pi users interact with every day.

What You’ll Do

• 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.
• Develop robust evaluation frameworks combining perceptual metrics, automated benchmarks, and user-facing quality signals.
• Contribute to Inflection’s research culture through publications, internal reviews, and knowledge sharing.

What We’re Looking For

• 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.
• Demonstrated ability to take a research idea from prototype to production: equally comfortable reading papers and writing efficient, CUDA-aware training loops.
• Familiarity with modern generative architectures for audio (e.g., diffusion models, autoregressive codecs, flow-matching) and their trade-offs.
• Clear, collaborative communication able to distill complex research into actionable insights for cross-functional partners.
• Have a bachelor’s degree or equivalent in Computer Science, Electrical Engineering, Linguistics, or a related field; MS or PhD strongly preferred.

Employee Pay Disclosures

At Inflection AI, we aim to attract and retain the best employees and compensate them in a way that appropriately and fairly values their individual contributions to the company. For this role, Inflection AI estimates a starting annual base salary to fall within the range of $225,000 to $325,000, depending on a candidate’s qualifications and level of experience. This role also includes a meaningful equity component, allowing employees to share in the long-term success of the company.

Benefits

Inflection AI values and supports our team’s mental and physical health. We are focused on building a positive, safe, inclusive and inspiring place to work. Our benefits include: 

• Diverse medical, dental and vision options 
• 401k matching program 
• Unlimited paid time off 
• Parental leave and flexibility for all parents and caregivers
• Support of country-specific visa needs for international employees living in the Bay Area