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Senior Data Scientist - Generative AI

Tecnoprism Pvt Ltd
5 - 9 Years
Anywhere in India/Multiple Locations

Posted on: 24/07/2026

Job Description

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.

Education :

- UG : Any Graduate

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