Hands-on experience with at least one major machine learning framework (PyTorch, TensorFlow, Keras).
- Familiarity with LLMs, prompt engineering, and fine-tuning (e.g., LoRA, QLoRA).
- Exposure to RAG systems and basic knowledge of hybrid search techniques.
- Understanding of model deployment and containerization (Docker).
- Proficiency in Python for AI development, data preprocessing, and scripting.
- Experience with generative AI tools (LangChain, Hugging Face, LlamaIndex) is a plus.
- Understanding of version control systems (Git).
- Awareness of AI compliance, data privacy, and responsible AI principles. mplement and fine-tune generative AI models under the guidance of senior team members.
- Contribute to prompt engineering and development of AI-powered workflows.
- Assist with the deployment, monitoring, and maintenance of AI models in production environments.
- Collaborate with data scientists and engineers to ensure seamless integration of AI capabilities.
- Perform data preprocessing, feature engineering, and API development for AI applications.
- Participate in code reviews, testing, and documentation to ensure quality and reliability.
- Stay updated with advancements in GenAI and share relevant learnings with the team. Required Soft Skills:
- Strong teamwork and communication abilities.
- Willingness to learn new AI/ML technologies and frameworks.
- Analytical mindset and attention to detail.
- Openness to feedback and continuous improvement. Qualifications:
- Bachelor's degree or Master's degree in Computer Science, Data Science, AI, or a related field.
- 3–5 years of professional experience in AI/ML development, with exposure to Generative AI.
- Experience delivering AI/ML projects in a collaborative setting.
- Exposure to cloud-based AI/ML environments (AWS, GCP, or Azure) is a plus.