Job Description & How to Apply Below
Work Location:
Pune and Bengaluru
Work Mode: 5days Office
Notice period:
Immediate to 15days
Roles & Responsibilities :
• Design and implement GenAI solutions using LLMs (e.g., GPT, LLaMA, Claude, Mistral) for enterprise use cases.
• Fine-tune and optimize pre-trained models for domain-specific tasks.
• Develop RAG pipelines using vector databases (e.g., Pinecone, FAISS, Weaviate) and embedding models.
• Integrate GenAI into applications via APIs, orchestration frameworks (e.g., Lang Chain, Llama Index), or custom interfaces.
• Collaborate with data scientists, MLOps engineers, and product teams to product ionize and scale GenAI solutions.
• Implement responsible AI practices, including safety filters, prompt engineering, bias mitigation, and model evaluation.
• Continuously evaluate and benchmark emerging open-source and commercial models for performance, cost, and alignment.
Years of
Experience:
• 8 – 13 years of hands-on experience in Generative AI.
Educational Qualification & Certifications (Optional):
• Bachelor’s or Master’s degree in Computer Science, AI/ML, or related field.
• Relevant certifications in AI/ML or cloud platforms preferred. V. Skill Set
Required:
Must Have:
• 8+ years in AI/ML, with at least 3–5 years focused on Generative AI or NLP.
• Proficiency in Python, transformers (Hugging Face), PyTorch or Tensor Flow.
• Expertise in LLMs, prompt engineering, and fine-tuning techniques (LoRA, PEFT, QLoRA).
• Strong understanding of embeddings, tokenization, vector search, and retrieval systems.
• Familiarity with GenAI toolkits like Lang Chain, Llama Index, or OpenAI API.
• Experience deploying models on cloud platforms (Azure, AWS, GCP) and working with MLOps tools.
Nice to Have:
• Knowledge of RAG architectures and vector databases (Pinecone, FAISS, Weaviate).
• Exposure to responsible AI practices and model evaluation frameworks.
Position Requirements
10+ Years
work experience
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