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Salary
$22k – $66k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Middle · 3+ years exp
Overview
Company
Impact
Profile match
Cartesia is an artificial intelligence research and technology company that builds real-time, low-latency generative voice models for interactive applications. Founded by Stanford researchers, the company utilizes State Space Models (SSMs) to power its flagship text-to-speech platform, Sonic, which enables sub-second voice synthesis, instant voice cloning, and emotional expression across dozens of languages. By providing real-time speech generation and voice agent infrastructure, Cartesia allows developers and enterprises to power conversational AI systems, virtual assistants, and customer service platforms.

We're opening our first-ever office in India and looking to hire a Software Engineer to advance our mission of building real-time multimodal intelligence.

Responsibilities:

  • Design and build a low-latency, scalable, and reliable model inference and serving stack for our cutting edge SSM foundation models.
  • Work closely with our research team and product engineers to translate cutting-edge research into incredible products.
  • Build highly parallel, high-quality data processing and evaluation infrastructure for foundation model training.
  • You'll have significant autonomy to shape our products and directly impact how cutting-edge AI is applied across various devices and applications.

Requirements:

  • Strong engineering skills, comfortable navigating complex codebases and monorepos.
  • A minimum of 3-5 years of experience in software engineering, product engineering or ML platform engineering
  • An eye for craft and writing clean and maintainable code.
  • You're comfortable diving into new technologies and can quickly adapt your skills to our tech stack (Go and Python on the backend, Next.js for the frontend).
  • Experience building large-scale distributed systems with high demands on performance, reliability, and observability.
  • Technical leadership with the ability to execute and deliver zero-to-one results amidst ambiguity.
  • Background in or experience working with machine learning and generative models.
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