Generative AI Engineer (NCS/Job/ 1990)

Generative AI Engineer

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

 

What We Offer

Cutting-Edge Technology:

· Access to premium GPU clusters A100s for training and experimentation

· Latest hardware and software tools to support your research and development

· Freedom to explore breakthrough AI technologies and methodologies

· Work on groundbreaking problems that haven't been solved before

· Collaborate with world-class researchers and engineers from top universities and tech companies

· Contribute to open-source projects and publish your research

 

 

Keywords

 

Python, Gen AI, LLM, Deep Learning, MLOps, LoRA, QLoRA, PyTorch