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Job Description: Required Qualifications & Skills: Technical Skills: - Programming: Expert proficiency in Python and deep familiarity with asynchronous programming. - Deep Learning Frameworks: Extensive experience with PyTorch (preferred) or TensorFlow. - GenAI Stack: Hands-on experience with Hugging Face ecosystem (Transformers, Accelerate, PEFT, Diffusers) and LangChain or LlamaIndex. - Inference Optimization: Practical knowledge of quantization methods and high-throughput serving frameworks (e.g., vLLM). - Infrastructure: Proficiency with Docker, Kubernetes, and cloud platforms (AWS, GCP, or Azure) specifically for GPU-accelerated workloads. - Math & Theory: Strong foundation in linear algebra, probability, and the mathematical mechanics of Transformer architectures. Roles & Responsibilities: 1. Generative AI Development: - Work with various model architectures (Transformer-based, Diffusion models, etc.) to solve complex business problems. - Evaluate model performance using specialized metrics (Perplexity, BLEU, ROUGE, or custom LLM-as-a-judge frameworks). 2. AI Inference Engineering: - Optimize model architectures for efficient deployment, focusing on reducing latency and memory footprint. - Implement inference optimization techniques including Quantization (GGUF, AWQ, GPTQ), Pruning, and Knowledge Distillation. - Utilize high-performance inference engines and frameworks such as TensorRT, vLLM, ONNX Runtime, or DeepSpeed-Inference. - Design scalable serving infrastructures using tools like NVIDIA Triton Inference Server, BentoML, or Ray Serve. - Optimize GPU utilization and memory management for large-scale model serving. 3. Data & Model Lifecycle: - Curate and preprocess large-scale datasets for pre-training, fine-tuning, and RLHF (Reinforcement Learning from Human Feedback). - Build automated pipelines for model evaluation and continuous monitoring of production models (detecting drift or hallucinations). - Collaborate with ML Engineers to integrate models into scalable microservices. Role: IT & Information Security - Other Education: - UG: Any Graduate .
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