About the Role
Key Responsibilities
Model Development & Optimization: Design, train, and fine-tune Generative AI models, such as GPT, LLaMA, Stable Diffusion, and DALL·E, for various applications, including text, image, and video generation.
Deep Learning Research & Implementation: Stay at the forefront of AI advancements by researching, experimenting, and implementing state-of-the-art techniques in transformers, LLMs, diffusion models, and reinforcement learning.
Data Engineering & Preprocessing: Work with large-scale datasets, ensuring high-quality preprocessing, augmentation, and synthetic data generation to improve AI model performance.
Inference & Deployment: Optimize model inference for efficiency and cost-effectiveness using techniques like quantization, pruning, and model distillation. Deploy models in production using cloud platforms (AWS, GCP, Azure) and containerized environments (Docker, Kubernetes).
API & Tool Development: Build and integrate APIs for AI-powered applications, ensuring seamless interaction between AI models and end-user applications.
Collaboration & Documentation: Work closely with engineers, researchers, and business stakeholders to align AI solutions with company goals. Maintain clear documentation and share knowledge with the team.
Requirements
Experience:
3+ years of hands-on experience with deep learning, LLMs, or generative AI models.
Educational Background:
Bachelor's, Master's, or Ph.D. in Computer Science, AI, Machine Learning, or related field.
Technical Skills:
Strong proficiency in Python, PyTorch, TensorFlow, JAX
Deep understanding of transformer architectures (BERT, GPT, T5, LLaMA, etc.)
Familiarity with vector databases (FAISS, Pinecone, Weaviate, ChromaDB)
Experience with LLM fine-tuning, RLHF, LoRA, and retrieval-augmented generation (RAG)
Strong grasp of MLOps, cloud deployment, and containerized environments
Preferred Qualifications
Experience with open-source LLMs (Mistral, Falcon, Mixtral, etc.)
Knowledge of AI ethics, bias mitigation, and responsible AI
Experience with multimodal AI models (text-to-image, text-to-video)
Background in distributed computing and model parallelism
About the Company
We are seeking a Generative AI Engineer to design, develop, and optimize cutting-edge AI models for real-world applications. The ideal candidate has deep expertise in machine learning, NLP, and deep learning frameworks, with a strong background in transformer-based architectures and large-scale AI model training. You will collaborate with cross-functional teams, including data scientists, software engineers, and product managers, to deploy AI-driven solutions that drive innovation and business impact.