AI Deployment & Optimization

30 interview prep topics with adaptive MCQ tests.

Model Serving
Model serving is the critical engineering discipline of deploying trained AI models as production-grade, low-latency,…
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vLLM
vLLM is the industry-leading open-source library for high-throughput, memory-efficient LLM inference and serving.…
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Quantization
Quantization is the process of reducing the numerical precision of model weights and/or activations, from FP32 or BF16…
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Multimodal AI
Multimodal AI represents the frontier of machine learning in 2026, systems that process, reason about, and generate…
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Batch Inference APIs
Batch Inference APIs represent a critical paradigm in modern AI infrastructure, moving away from low-latency,…
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Chunked Prefill
Chunked Prefill is a critical architectural optimization in modern LLM serving systems designed to mitigate the…
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Continuous Batching
Continuous batching is a critical inference optimization technique that allows LLM serving engines to dynamically batch…
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Disaggregated Prefill-Decode Serving
Disaggregated prefill-decode serving is a critical architectural pattern in modern LLM inference, designed to solve the…
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GPU Memory Bandwidth Bottlenecks
GPU memory bandwidth bottlenecks occur when the rate at which data is transferred between high-bandwidth memory (HBM)…
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GPU SRAM vs HBM
In the era of large-scale transformer models, the performance of GPU-accelerated workloads is increasingly dictated by…
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Inference Latency vs Throughput
In the landscape of 2026 AI engineering, balancing inference latency and throughput is the defining challenge of model…
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Knowledge Distillation for LLMs
Knowledge Distillation (KD) for Large Language Models is a critical model compression technique used to transfer the…
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Model Compilation (torch.compile, XLA)
Model compilation is the process of transforming high-level deep learning code into optimized, hardware-specific…
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Model Parallelism (Tensor and Pipeline)
Model parallelism is a critical technique in 2026 for deploying Large Language Models (LLMs) that exceed the memory…
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Model Warm-Up Strategies
Model warm-up strategies are essential techniques in 2026 for maintaining low-latency inference in production AI…
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Multi-LoRA Serving (S-LoRA)
Multi-LoRA serving, often exemplified by the S-LoRA architecture, is a critical technique in 2026 for deploying…
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NCCL and Multi-GPU Communication
The NVIDIA Collective Communications Library (NCCL) is the industry-standard framework for high-performance…
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ONNX Runtime
ONNX Runtime (ORT) is a high-performance inference and training engine designed to accelerate machine learning models…
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PagedAttention
PagedAttention is a critical memory management algorithm designed to solve the KV cache fragmentation problem in LLM…
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Prompt Caching
Prompt Caching is a critical optimization technique in 2026 for large-scale LLM deployments, allowing developers to…
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Prompt Compression Techniques
Prompt compression techniques are essential engineering methodologies designed to reduce the size of input prompts…
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Speculative Decoding
Speculative Decoding is a critical optimization technique in 2026 for reducing LLM inference latency by leveraging a…
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Synthetic Data Generation for Fine-Tuning
Synthetic Data Generation for Fine-Tuning has become a cornerstone of modern AI engineering, particularly as…
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TensorRT-LLM
TensorRT-LLM is an open-source library by NVIDIA designed to accelerate and optimize LLM inference on NVIDIA GPUs. In…
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Time to First Token (TTFT)
Time to First Token (TTFT) is the critical latency metric measuring the duration between a client sending a request to…
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Triton Inference Server
Triton Inference Server is an open-source inference serving software that enables teams to deploy trained AI models…
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DeepSpeed Optimization Library
The DeepSpeed Optimization Library has established itself as an indispensable tool for distributed deep learning,…
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Ollama Local LLM Scaling
The domain of local Large Language Model (LLM) scaling involves deploying, orchestrating, and optimizing lightweight…
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Ray Distributed Computing
Ray distributed computing has emerged as the definitive orchestration engine for scaling artificial intelligence,…
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Text Generation Inference
Text Generation Inference (TGI) is a production-grade, highly optimized framework developed by Hugging Face…
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