Inference Systems Engineer
LambdaQ labs Pvt. Ltd. · Not specified · onsite · Posted 55d ago
Undisclosed3–7 yrsfulltimeSourced from
About a minute. You'll make an account on the way through.
About this role
About The Role You'll build and optimize the serving stack that makes Vikasit Inference fast, reliable, and affordable at India scale — kernels, batching, caching, and the OpenAI-compatible API surface developers love. What you'll do
- —Optimize throughput and latency across our model fleet (vLLM / SGLang / TensorRT-LLM)
- —Build batching, KV-cache, quantization, and routing for MoE models
- —Own reliability, autoscaling, and cost of the inference platform
- —Keep the OpenAI-compatible API rock-solid for streaming and tool calls What we're looking for
- —Deep systems engineering (GPU, CUDA-adjacent, or high-performance serving)
- —Experience with an LLM serving framework in production
- —Comfort owning latency, throughput, and cost SLOs Nice to have
- —CUDA / Triton kernels
- —Quantization (GGUF, AWQ, FP8)
- —Multi-region infra Sound like you? We hire for skill over credentials. Tell us why you're a fit — links and projects welcome. Apply for this role
Sourced from linkedin
Skills
CudacachingvLLMTritonGPUOpenAI SDKQuantizationBatchingSGLangTensorRT-LLMAWQGGUFFP8Triton kernelsMoE modelsKV CacheOpenAI-compatible APImulti-region infraRoutingHigh-performance servingLLM serving frameworkAutoscalinginferenceKernels