Inference Jobs

Together AI

This research engineering role focuses on translating new Reinforcement Learning (RL) algorithms, scheduling methods, and inference optimizations into production-grade systems that power Together's API. The Core ML team operates at the intersection of efficient inference (algorithms, architectures, engines) and post-training/RL systems, building and maintaining high-performance inference and RL engines at production scale. The goal is to significantly improve model speed, cost-efficiency, and capabilities through RL-based post-training. This position requires a blend of algorithmic understanding and systems engineering, with opportunities to work across the entire stack from RL algorithms and training engines to kernels and serving systems, ultimately driving measurable improvements in latency, throughput, cost, and model quality at scale.

$200k - $280k

Mistral AI

Mistral AI is seeking an Applied AI Engineer to drive the adoption of its products among customers and collaborate with them to address complex technical challenges. This role is integral to the Applied AI Engineering team, focusing on successful deployment of Mistral AI products and building complex enterprise use-cases. You will work hand-in-hand with customers from pre-sale to post-implementation, ensuring solutions meet and exceed client expectations. You will manage customer relations involving multiple stakeholders and serve as a key resource in externalizing our research into production settings.

Mistral AI

Mistral AI is seeking an Applied AI Engineer to drive the adoption of its products among customers and collaborate with them to address complex technical challenges. This role is integral to the Applied AI Engineering team, focusing on the successful deployment of Mistral AI products and building complex enterprise use-cases. You will work hand-in-hand with customers from pre-sale to post-implementation, ensuring solutions meet and exceed client expectations. You will manage customer relations involving multiple stakeholders and serve as a key resource in externalizing our research in production settings.