Remote AI Kernel & Inference Engineer (Low-Latency)

Tuxcare Inc.; Ciudad de Mendoza; Remote; ARS 184,482,000 - 276,723,000; Full time

Job summary

Tether is seeking an AI Research Engineer (Kernel & Inference Optimization) to advance model serving and inference architectures for next-gen AI systems. You will optimize deployment and inference strategies across devices from edge to cloud, focusing on low latency and memory efficiency.

The role requires deep expertise in designing robust inference pipelines, experimental evaluation, and collaboration with cross-functional teams.

Qualifications

• Degree in Computer Science or related field; PhD preferred.
• Experience in model serving and inference optimization on mobile devices.
• Strong publication record in AI R&D is a plus.

Responsibilities

• Design and deploy state-of-the-art model serving architectures with high throughput and low latency.
• Build, run, and monitor controlled inference tests in simulated and live environments.
• Identify and prepare high-quality test datasets and simulations for real-world deployment.
• Analyze computational efficiency and diagnose bottlenecks in the serving pipeline.
• Collaborate with cross-functional teams to integrate optimized serving frameworks into production pipelines.

Skills

MSL (Metal Shading Language)

GPU kernel programming

Low-latency inference

Model serving pipelines

Edge/mobile deployment

C/C++

Education

PhD in NLP or Machine Learning

Bachelor's degree in Computer Science

Tools

Metal Shading Language (MSL)

Job description

Tether is seeking an AI Research Engineer (Kernel & Inference Optimization) to advance model serving and inference architectures for next-gen AI systems. You will optimize deployment and inference strategies across devices from edge to cloud, focusing on low latency and memory efficiency.

The role requires deep expertise in designing robust inference pipelines, experimental evaluation, and collaboration with cross-functional teams.