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We're committed to bringing passion and customer focus to the business.*
Responsibilities
Design and implement advanced solutions utilizing Large Language Models (LLMs).
Demonstrate self\-driven initiative by taking ownership and creating end\-to\-end solutions.
Conduct research and stay informed about the latest developments in generative AI and LLMs.
Develop and maintain code libraries, tools, and frameworks to support generative AI development.
Participate in code reviews and contribute to maintaining high code quality standards.
Engage in the entire software development lifecycle, from design and testing to deployment and maintenance.
Collaborate closely with cross\-functional teams to align messaging, contribute to roadmaps, and integrate software into different repositories for core system compatibility.
Possess strong analytical and problem\-solving skills.
Demonstrate excellent communication skills and the ability to work effectively in a team environment. Primary Skills:
Natural Language Processing (NLP): Hands\-on experience in use case classification, topic modeling, Q\&A and chatbots, search, Document AI, summarization, and content generation. AND/OR
Computer Vision and Audio: Hands\-on experience in image classification, object detection, segmentation, image generation, audio, and video analysis.
Cloud: Hands\-on experience with cloud platforms such as Azure, AWS, and GCP. Cloud certification is preferred. • Application Development: Proficiency in Python, Docker, FastAPI/Django/Flask, and Git.
If you like wild growth and working with happy, enthusiastic over\-achievers, you'll enjoy your career with us!
### **Hiring Related Queries**
India: HiringsupportIndia@fractal.ai
Outside India: HiringsupportROW@fractal.ai
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Generative AI: o Proficiency with SaaS LLMs, including Lang chain, llama index, vector databases, Prompt engineering (COT, TOT, ReAct, agents). Experience with Azure OpenAI, Google Vertex AI, AWS Bedrock for text/audio/image/video modalities. o Familiarity with Open\-source LLMs, including tools like TensorFlow/Pytorch and huggingface. Techniques such as quantization, LLM finetuning using PEFT, RLHF, data annotation workflow, and GPU utilization.