Company Description

Smallest AI is one of the world’s fastest-growing speech AI research companies. We have some of the world’s best speech AI models and we are powering over 30,000 customers across 12 different countries to automate their calling operations. At heart, we are engineers, researchers, and a bunch of nerds who love diving deep into AI.

Role
You’ll work deeply at the intersection of model architecture, GPU optimization, and real-time speech systems. Expect to profile models on different GPU setups, optimize kernels, experiment with new architectures, and push the limits of speed + efficiency.

What You’ll Do

Dive into model architectures (ASR / TTS / SLMs) and optimize them for specific GPUs and hardware profiles
Build, debug, and tune kernels using CUDA / Tinygrad / AMD toolchains
Convert, optimize, and benchmark models using TensorRT, ONNX, and other inference engines
Work hands-on with PyTorch to train, fine-tune, and evaluate real-time speech models
Run large-scale experiments, manage datasets, and analyze model performance at scale
Productionize models for ultra-low latency speech workloads
Collaborate with research, infra, and product teams to push models into production

Requirements

Strong experience with CUDA, Tinygrad, AMD GPU toolkit, or similar low-level GPU programming stacks
Hands-on proficiency with PyTorch and Python
Deep understanding of neural networks, training dynamics, and optimization
Experience handling and processing large datasets
Familiarity with production inference pipelines
Strong problem-solving skills with ability to go deep into performance bottlenecks

Great to Have

Experience training speech models (ASR, TTS, SSL, etc.)
Familiarity with audio encoders, decoders, waveform models
Experience with MLOps, experiment tracking, deployment pipelines
Training or fine-tuning models for production / published papers
Experience with TensorRT and ONNX Runtime

Data Scientist (Speech)