Key Responsibilities :
- Design, develop, and deploy generative AI models and systems that solve complex business problems.
- Research and implement state-of-the-art algorithms in natural language generation, image synthesis, or other generative AI domains.
- Collaborate closely with data scientists, ML engineers, and product teams to integrate generative AI capabilities into applications and platforms.
- Optimize model performance, scalability, and robustness for production environments.
- Experiment with novel architectures, fine-tuning methods, and data augmentation techniques to improve model outputs.
- Ensure compliance with ethical AI practices and data privacy standards.
- Stay up-to-date with the latest advancements in generative AI research and industry trends.
Required Qualifications & Skills :
Minimum 7 years of experience in AI / ML engineering, with a focus on generative models.Strong programming skills in Python and familiarity with ML frameworks like TensorFlow, PyTorch, or JAX.Hands-on experience with transformer architectures (e.g., GPT, BERT) and generative model types (GANs, VAEs, diffusion models).Expertise in data preprocessing, model training, hyperparameter tuning, and deployment of ML models.Solid understanding of NLP, computer vision, or multimodal AI techniques.Experience with cloud platforms (AWS, GCP, Azure) for model training and serving.Strong problem-solving abilities and research mindset.Preferred Qualifications :
Advanced degree (Masters or PhD) in Computer Science, Artificial Intelligence, Machine Learning, or related fields.Contributions to open-source AI projects or published research papers in generative AI.Knowledge of AI ethics, bias mitigation, and responsible AI development(ref : hirist.tech)