TFLite Jobs

Figure is an AI robotics company developing autonomous general-purpose humanoid robots with the goal of shipping robots with human-level intelligence. These robots are engineered to perform a variety of tasks in home and commercial markets. We are seeking a Staff AI Inference & Acceleration Engineer to join our Platform Software team. This role will be responsible for the on-board inference architecture for our humanoid robots, acting as the technical authority on how AI workloads are mapped, optimized, and executed across the robot's compute hardware. The primary objective is to reduce power consumption and cost while meeting strict latency and reliability demands for a real-time autonomous system.

$180k - $275k

Deepgram is seeking an Applied ML Engineer to focus on deploying their advanced speech models to a variety of edge devices and non-NVIDIA accelerators. This role involves adapting existing models to run efficiently within diverse hardware constraints, including different inference runtimes and operator sets. You will be responsible for optimizing models through techniques like quantization and precision adjustments, validating performance on real hardware, and building robust deployment pipelines for edge targets. This is a hands-on engineering position, distinct from research or cloud-focused roles, aimed at ensuring Deepgram's cutting-edge voice AI can be deployed effectively across a wide range of customer hardware.

$155k - $245k

Deepgram is seeking an Embedded AI Engineer to work on optimizing their speech models for a wide range of hardware, including non-NVIDIA accelerators, embedded SoCs, mobile processors, and specialized devices with tight resource constraints. This role operates at the lowest layer of the edge stack, focusing on writing and optimizing custom kernels and operators, collapsing models onto device-specific execution units, and performing target-side quantization and assembly-level tuning. The engineer will collaborate with Applied ML Engineers to ensure Deepgram's models can run efficiently on new hardware platforms, making them viable for edge deployment. This position is ideal for senior embedded engineers with a passion for AI or staff-level engineers looking to shape the future of on-device AI model deployment.

$219k - $274k