Key Responsibilities:
• Implement 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 Technical Skills:
• 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.
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.
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