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Urgent! Generative AI Engineer Job Opening In Bengaluru – Now Hiring Confidential

Generative AI Engineer



Job description

About This Role

We're seeking a passionate Generative AI Engineer & problem solver to join our world-class team of innovators who are pushing the boundaries of what's possible with artificial intelligence.

You'll be at the forefront of cutting-edge AI research and development, working on awesome projects.

What You'll Do

Core Responsibilities:

·        Collaborate with cross-functional teams to translate complex AI concepts into practical business solutions.

·        Design systems around open source, enterprise models like Llama, Gemini, GPT to solve innovative problems.

·        Build robust evaluation pipelines to assess model performance, safety, and alignment with business objectives.

·        Optimize model latency and performance for real-time applications and large-scale deployment

·        Architect scalable ML infrastructure for training, inference, and model serving

·        Fine-tune Large Language Models (LLMs) and other transformer-based architectures

·        Ability to explain complex AI concepts to technical and non-technical stakeholders

What We're Looking For

Experience Requirements:

·        6+ years of overall data science or ML experience.

·        1.5+ years of hands-on experience with generative AI and large language models.

·        Advanced degree in Computer Science, Machine Learning, or related field.

·        Experience in taking ML/DL model to production.

 

️ Technical Expertise:

 

·        Python, C++ or any other high-level language.

·        PyTorch and TensorFlow.

·        Experience with Hugging Face Transformers, LangChain, LlamaIndex, Pydantic AI

·        Deep Learning fundamentals: neural networks, backpropagation, optimization

·        Generative AI frameworks: OpenAI API, Anthropic Claude, Google Gemini, local LLM deployment

·        Model architectures: Transformers, attention mechanisms, encoder-decoder models

·        Fine-tuning techniques: LoRA, QLoRA, full parameter fine-tuning, RLHF

·        Design and implement comprehensive evaluation pipelines

·        A/B testing for AI systems and statistical significance testing

·        Latency optimization techniques: model quantization, pruning, distillation

·        Experience with MLOps tools: MLflow, Weights & Biases, DVC


Skills Required
Python, Llm, Deep Learning, MLops, Pytorch


Required Skill Profession

Computer Occupations



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