Hire freelance Generative AI developers in India
Generative AI developers looking for their next gig. Juniors to seniors and everyone in between, you'll find them all here.
Langchain or llama index, those are just integrations. From fine tuning LLM for specific use case to deploying it as a system and integrating all these tools is all I do these days.
Hello everyone I started my ML journey back in late 2020 when I saw this connection between my high school math topics (like calculus, linear algebra, etc) with how neural networks work. 18-year-old me, started his journey with Andrew Ng's famous deep learning course. My early days were very much focussed on how each part of deep learning works, for example How a neuron works How convolution as an operation works How does backpropagation exactly work, etc I even wrote my first blog on medium describing the nuts and bolts of neural networks and their different types. There was a time in mid 2021, I got to learn about Graph Machine Learning. Being so fascinated, I did the same for Graph ML, like how I did for general ML and deep learning. I even ended up doing a research internship on Graph Variational Autoencoder for recommendation systems. I ended up writing my second research paper. Fast forward, I slowly started to hear this buzzword called "deployment". Initially, I thought of uploading my model file to the cloud. But it was much more than that. Slowly I started to gain knowledge about ML system design and how the backend and ML work in sync. How we can serve our ML apps by creating APIs, dockerizing them, and then deploying them on cloud services. Then I got into Major League Hacking Prep Program and I learned so much about remote work and collaborating with open source. Just after that, I got my industrial internship at a startup called voxela.ai where I learned so much about computer vision and object recognition and how it is deployed on an enterprise basis. I also learned about quantization and how to convert these models into TensorRT for fast serving. Fast forward we saw the rise in Large Language Models after the advent of chatGPT. We are seeing now so many people making tools using that in just one night and things getting viral. I always believed that it was always a bubble. And yes, I was right when I got to learn from experts that it was more about making a long-term, reliable, and efficient product with LLMs. Currently, I am working as a data science engineer intern at CorridorPlatforms. Being very interested in LLMs, I have explored and incorporated the LLM lifecycle, from fine-tuning an LLM with 4-bit quantization to compressing it further to run on a C++ backend and then serving it, doing prompt engineering for better performance, using knowledge bases to provide better context for document Q&A, to doing different LLM evaluation strategies for better and governed LLM systems. This journey has been very beautiful and remarkable for me. I believe that nothing is permanent, we are right now in an era where things are changing very fast. However it's not ONLY LLMs or ONLY Diffusion models, and we can never say classical ML is not gonna stay. Real ML is the balanced combination of everything and it's just putting the correct choice in the right place and attaching the important strings such that everything can work in sync and seamlessly. I look forward to working and helping organizations to apply my learnings and also learning more. Thanks
LangChain | FlowiseAI | ChatGPT | Prompt Engineering |Full Stack Developer
As a skilled and versatile full-stack developer with a strong background in AI and prompt engineering, I am adept at crafting cutting-edge AI-powered applications that deliver innovative solutions to real-world challenges. With a keen understanding of both front-end and back-end development, I bring a holistic approach to building dynamic and intuitive web applications. My proficiency in AI technologies allows me to leverage generative models, Langchain, and FlowiseAI to create intelligent and interactive user experiences. Whether it's designing chatbots that provide personalized responses, implementing recommendation systems, or enabling predictive analytics, I have the expertise to incorporate AI seamlessly into projects.
I'm a versatile full-stack developer with a knack for AI and automation. Passionate about tackling complex challenges, I thrive on creating efficient, robust, and scalable solutions using a wide array of technologies and frameworks.
I'm Tanush Yadav, a full-stack developer with over three years of industry experience. My professional journey is decorated with diverse projects that have sharpened my skills and broadened my proficiency in multiple languages and frameworks. My development adventure began with Python, lured by its readability and versatility. This led me to work on a variety of projects spanning domains such as education and cybersecurity, reinforcing the importance of adaptability and problem-solving in the field of technology. My path then took a turn towards the development of Learning Management Systems and Quiz Platforms for Progressive Minds, using Django and React. My journey then extended to MERN stack where I worked on several platforms like Practus and KoinPR. One of my notable assignments was with Mavex AI, where I was part of the team transitioning from Python utilities and DialogFlow to a LangChain system. This shift not only optimized our scheduling and user-input systems but also played a crucial role in securing pre-seed funding. Most recently, I was associated with CloudDefense.ai, where I worked on developing secure AWS policies for users via Python and CloudTrail. This demanding task culminated in the successful launch of a live CIEM feature. My technical skill set is diverse and encompasses Python and Django for backend tasks, and Node.js & Express.js for server-side operations. When it comes to frontend development, I am proficient in both React and Vue.js. Moreover, I utilize FastAPI for creating APIs, especially during the transition from scripts to APIs. I am adept at navigating these and other technologies to deliver robust and efficient solutions. I firmly believe that the technology industry demands continuous learning and adaptability, and I am always up for such challenges. I look forward to applying my unique amalgamation of skills and experiences to contribute to my next role.
AI/ML & NLP Practitioner | ⚙️MLops
🤖 I'm an student pursuing a degree in Data Science and Artificial Intelligence immersing myself in the world of AI. As an AI/ML practitioner and NLP professional with a deep passion for the field of Artificial Intelligence and Machine Learning (AI/ML). With a focus on Natural Language Processing (NLP). ⚙️ In addition to my NLP proficiency, I have experience in MLops (Machine Learning Operations). This enables me to optimize the end-to-end lifecycle of ML models, from designing scalable pipelines to ensuring robust deployment, monitoring, and maintenance. 💡 Furthermore, I have developed a quite good experience with Large Language Models (LLMs). I have dedicated considerable time and effort to understanding their architecture and leveraging their capabilities. LLMs can tackle challenging NLP tasks, such as language generation, summarization, sentiment analysis and unlocking new possibilities. ⚡️ I am currently collaborating with the Advanced Engineer School to advance the field of code analysis and code documentation generation through the development of a new framework. with this collaboration I will get the opportunity to delve deeper into the realm of large language models (LLMs) 🌐 Looking ahead, I am always open to collaboration. If you have an innovative idea that requires the expertise of an AI/ML and NLP. Let's connect and create something remarkable together, harnessing the potential of AI to make a meaningful difference in the world! LinkedIn :linkedin.com/in/khush-patel-kp