We’re looking for a Senior AI/ML Research Engineer to work on large-scale AI inference, synthetic data generation, and distributed training systems.
This is a hands-on research and engineering role for someone who has built infrastructure supporting large-scale AI models and wants to work on difficult problems across inference performance, distributed systems, reinforcement learning, and synthetic data.
No third parties
What You’ll Do
Design and build large-scale synthetic data generation pipelines and orchestration systems.
Optimize AI inference workloads for performance, cost, memory, and compute utilization.
Build and improve distributed inference infrastructure for large-scale AI models.
Contribute to open-source libraries and frameworks for synthetic data generation and distributed reinforcement learning.
Research and implement new approaches to model inference, training, and post-training.
Collaborate with researchers and engineers working on large-scale AI systems.
Contribute research suitable for publication at conferences such as ICML and NeurIPS.
Translate highly technical work into clear technical content for developers and users.
Stay current with advances in AI infrastructure, distributed inference, synthetic data, and model optimization.
What We’re Looking For
Experience with one or more of the following is especially valuable:
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