We are leveraging diffusion technology to develop a new generation of LLMs. Our dLLMs are much faster and more efficient than traditional autoregressive LLMs. Backed by AI Grant and Amplify.
About the role
We're looking for engineers and scientists to design, optimize, and scale the systems that power our diffusion LLMs in production. Your work will make inference faster, more cost-effective, and more reliable.
What they're looking for
- Build and optimize high-performance model serving systems for low-latency inference of diffusion LLMs
- Extend orchestration frameworks (Kubernetes, Ray, SLURM) for distributed inference, evaluation, and large-batch serving
- Implement and manage load balancing, autoscaling, and traffic routing for model endpoints
- Build systems for model versioning, canary deployments, and zero-downtime rollouts
- Develop monitoring, alerting, and observability tooling to ensure SLA compliance and rapid incident response
- Collaborate with ML researchers to translate model advances (new architectures, quantization techniques, batching strategies) into production-ready serving improvements
More about this role
Inception creates the world’s fastest, most efficient AI models. Our Mercury model is the world’s fastest reasoning LLM and first commercially available diffusion LLM, delivering 5x greater speed and efficiency than today’s LLMs, with best-in-class quality.
We are the AI researchers and engineers behind such breakthrough AI technologies as diffusion models, flash attention, and DPO.
The Role
We're looking for engineers and scientists to design, optimize, and scale the systems that power our diffusion LLMs in production. Your work will make inference faster, more cost-effective, and more reliable.
Key Responsibilities
- Build and optimize high-performance model serving systems for low-latency inference of diffusion LLMs.
- Extend orchestration frameworks (Kubernetes, Ray, SLURM) for distributed inference, evaluation, and large-batch serving.
- Implement and manage load balancing, autoscaling, and traffic routing for model endpoints.
- Build systems for model versioning, canary deployments, and zero-downtime rollouts.
- Develop monitoring, alerting, and observability tooling to ensure SLA compliance and rapid incident response.
- Collaborate with ML researchers to translate model...
Browse similar: AI jobs · AI startup jobs · Startup jobs · San Francisco Bay Area