Data Scientist
4 weeks ago
We are seeking a skilled and innovative Data Scientist to join our team, specializing in the development of AI agents, Retrieval-Augmented Generation (RAG) models, and cutting-edge technologies like LangChain and OpenAI. This is a hands-on role where you will leverage large language models (LLMs) to build intelligent systems that can handle complex tasks and provide actionable insights. You will work alongside engineers and product teams to design, deploy, and optimize AI models that integrate both structured and unstructured data.
Location : Mumbai City (Work from Office Only) Only Candidates that Can meet this requirement, may apply
Key Responsibilities :
AI Agent Design & Development :
- Design and develop intelligent AI agents using OpenAI GPT models, LangChain, and other advanced LLMs (e.g., GPT-4, future models like Gemini and Llama).
- Implement and optimize multi-agent systems that leverage RAG (Retrieval Augmented Generation) techniques to access and utilize external data sources for enhanced agent performance.
- Collaborate with the engineering team to build AI agents capable of completing complex tasks autonomously.
- Develop, train, and fine-tune machine learning models for various applications, including natural language processing (NLP), text generation, and reinforcement learning.
- Implement RAG frameworks to enable models to retrieve and incorporate real time contextual information from external data stores (e.g., FAISS, Pinecone).
- Design and deploy LLM-based solutions for various business problems, optimizing them for efficiency and accuracy.
- Clean, preprocess, and transform large datasets from both structured (SQL/NoSQL) and unstructured (text, documents, etc.) sources.
- Engineer features that improve model performance, particularly in the context of AI agents and LLMs.
- Develop data pipelines that support continuous updates to the agents knowledge base and ensure that agents have access to up-to-date information.
- Work closely with data engineers, product managers, and business teams to define project goals, build solutions, and integrate AI models into the company's product offerings.
- Communicate technical results and insights clearly to stakeholders, providing actionable recommendations based on data-driven insights.
- Stay up-to-date with the latest advancements in AI, NLP, machine learning, and RAG techniques.
- Explore and experiment with emerging AI frameworks like LangChain, OpenAI API, and others to improve model performance and capabilities.
- Contribute to R&D efforts to develop novel AI solutions and enhance the current system.
Technical Skills :
- Proficiency in Python for data analysis, machine learning, and model development.
- Experience with OpenAI models (e.g., GPT-3, GPT-4) and understanding of their use cases and limitations.
- Hands-on experience with LangChain (LangChain Tools), Hugging Face models, LLM and building multi-agent systems using this framework.
- Strong experience with machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
- Knowledge of RAG (Retrieval-Augmented Generation) techniques and tools like FAISS, Pinecone, or other vector databases for information retrieval.
- Familiarity with data visualization tools (e.g., Matplotlib, Seaborn, Tableau) to present findings effectively.
- Solid understanding of NLP techniques such as text generation, sentiment analysis, and language modeling.
- Good to have : Experience with cloud platforms like AWS, Google Cloud, or Azure for deploying models in production.
- Experience working with both SQL (e.g., PostgreSQL, MySQL) and NoSQL (e.g., MongoDB, Cassandra) databases.
- Understanding of data pipelines and ETL processes for handling large-scale datasets.
- Strong written and verbal communication skills, with the ability to explain technical concepts to non-technical audiences.
- Excellent problem-solving and analytical abilities with a focus on applying machine learning techniques to real-world business challenges.
- Familiarity with deep learning frameworks such as Keras, TensorFlow, and PyTorch for advanced AI applications.
- Good to have : Experience with big data technologies like Hadoop or Spark for processing large datasets.
- Knowledge of reinforcement learning (RL) and decision-making models for autonomous AI systems.
- Familiarity with deploying models and applications in production environments using tools like Docker, Kubernetes, and CI/CD pipelines.
- Bachelor's degree in Computer Science, Data Science, Mathematics, Statistics, Engineering, or a related field (Master's degree preferred)
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