We are seeking a talented AI/ML Engineer specializing in Generative AI to join our innovative team.

In this role, you will design, develop, and deploy state-of-the-art generative models that power next-generation AI applications across various domains.

You will work with large-scale datasets, cutting-edge machine learning frameworks, and collaborate closely with cross-functional teams to build scalable, efficient, and ethical AI solutions.

Key Responsibilities :

- Design, implement, and optimize generative AI models such as GANs, VAEs, Diffusion Models, and Large Language Models (LLMs) for diverse applications including text, image, audio, and video generation.

- Fine-tune pre-trained generative models to adapt them to specific business problems and datasets.

- Develop pipelines for training, evaluating, and deploying generative models at scale.

- Collaborate with data engineers to preprocess large-scale datasets and build efficient data pipelines.

- Build APIs and integration layers to embed generative AI capabilities into production systems.

- Research and implement advanced techniques for prompt engineering, model compression, and interpretability.

- Monitor model performance, troubleshoot issues, and continuously improve model accuracy and robustness.

- Ensure ethical AI use by implementing fairness, bias mitigation, and explainability practices.

- Stay current with the latest research and trends in generative AI and machine learning, and apply innovations to practical solutions.

- Document models, experiments, and workflows for reproducibility and knowledge sharing.

Qualifications & Skills :

- Bachelors or Masters degree in Computer Science, Artificial Intelligence, Machine Learning, or related field; PhD is a plus.

- Strong hands-on experience with generative AI models including GANs, VAEs, Diffusion Models, Transformers, and LLMs (e.g., GPT, BERT, T5).

- Proficiency with ML frameworks such as TensorFlow, PyTorch, Hugging Face Transformers, or similar.

- Experience in data preprocessing, augmentation, and pipeline development for large-scale datasets.

- Solid programming skills in Python and familiarity with containerization (Docker) and cloud platforms (AWS, GCP, Azure).

- Understanding of model deployment techniques including RESTful APIs and model serving frameworks (e.g., FastAPI, TorchServe).

- Knowledge of NLP, computer vision, or audio processing as applicable to generative models.

- Familiarity with ethical AI principles, model fairness, and bias mitigation techniques.

- Excellent problem-solving skills and ability to work independently and collaboratively in a fast-paced environment