Key Responsibilities:
- Design, develop, and implement machine learning models and algorithms for real-world applications.
- Research and experiment with Generative AI models (e.g., GPT, diffusion models, transformers) to solve complex problems.
- Collaborate in a culture of experimentation, contributing to PoCs, rapid prototyping, and iterative model development.
Build and maintain data pipelines and infrastructure in collaboration with Data Engineers. - Partner with cross-functional teams including product, engineering, and analytics to define AI/ML use cases and deliver impactful solutions.
- Analyze large-scale structured and unstructured datasets to identify trends, patterns, and opportunities.
- Evaluate and optimize model performance and reliability in production environments.
- Stay current on industry trends and emerging technologies in AI/ML and GenAI.
Skills Needed:
- Minimum 1+ years of hands-on experience in AI/ML and Generative AI projects.
- Proficiency in Python and common ML libraries (e.g., scikit-learn, TensorFlow, PyTorch, Hugging Face).
- Strong grasp of machine learning concepts, model development lifecycle, and performance evaluation.
- Experience working with transformer-based architectures and generative techniques like GANs, VAEs, or diffusion models.
- Familiarity with cloud platforms (e.g., AWS, GCP, or Azure) and MLOps tools.
- Excellent problem-solving, communication, and teamwork skills.
- Experience deploying models into production environments.
- Familiarity with LLM fine-tuning, prompt engineering, or synthetic data generation.
- Excellent communication and presentation skills are essential.
Experience
2 – 3 Years (1+ year of experience in AI/ML and Generative AI)
