We are seeking a skilled and innovative Generative AI Engineer with 4+ years of experience in machine learning and deep learning, including hands-on work with transformer-based models. You will be responsible for designing, developing, and deploying generative models for use cases such as text generation, image synthesis, code generation, and more. The ideal candidate has a strong foundation in AI/ML, deep learning frameworks, and experience fine-tuning and deploying large language models (LLMs) and diffusion models in production.
Key Responsibilities:
Design and implement generative AI solutions using models such as GPT, BERT, DALL E, Stable Diffusion, or custom transformer architectures.
Fine-tune pre-trained models on domain-specific data for improved performance.
Build scalable pipelines for training, evaluation, and deployment of generative models.
Collaborate with data scientists, ML engineers, and product teams to integrate AI solutions into products.
Stay current with the latest advancements in generative AI research and tools.
Optimize inference performance and ensure model compliance with ethical AI standards.
Required Qualifications:
Bachelor s or Master s degree in Computer Science, AI/ML, Data Science, or a related field.
4+ years of experience in machine learning, with at least 2+ years in generative AI or NLP.
Proficient in Python and ML libraries such as PyTorch, TensorFlow, Hugging Face Transformers, or LangChain.
Hands-on experience with foundation models (e.g., GPT-3/4, LLaMA, Claude, PaLM).
Experience with model fine-tuning, RLHF, LoRA, or quantization techniques.
Knowledge of prompt engineering and chaining techniques.
Familiarity with MLOps practices and cloud platforms (AWS, GCP, or Azure).