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Senior software engineer / Tech Leader / AI Enthusiast

I'm a software engineer passionate about innovation and pushing the boundaries of technology. While I have over 16 years of experience building web applications, my true passion lies in AI and generative frameworks. I'm currently focused on studying Langchain, Semantic Kernels, and leveraging LLM for code generation. I thrive in research and development roles where I can understand a business's challenges and needs, then prototype solutions using cutting-edge technologies. I naturally take on a researcher position in teams and love learning about new concepts that can drive innovation. While I may not always be the strongest explainer, I strive to become a source of knowledge for colleagues on AI and its applications. My leadership abilities are still developing, but I shine as an individual contributor who can advance a company's technological capabilities. I'm particularly interested in organizations looking to get ahead of the AI revolution. My experience with Python, C#, and Node.js allows me to build prototypes and proofs of concept, though I'm always eager to pick up new languages and frameworks. Outside of work, I continue to expand my knowledge of AI through side projects and independent research. I'm passionate about this emerging field and believe generative technologies will transform software engineering. I hope to find opportunities that allow me to work with other innovative thinkers in exploring AI's possibilities and building the future. Overall, my curiosity, technical skills, and vision for the impact of AI position me to thrive in research-focused roles at companies with ambitions for real innovation.

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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

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Senior Data Scientist: Machine Learning / AI

I am a data scientist with 7 years of experience as a freelancer in diverse industries. My mission is enabling my clients and the teams I work with to implement data-driven innovation, making the connection between use cases, algorithms, and the appropriate tech stack. I am mainly focused on machine learning from prototype to deployment, but my work also regularly involves optimization and data mining. Data-driven Innovation – end-to-end To make data-driven innovation succeed, I work with my clients in all phases of a data science project – including business case discovery, structuring of requirements, selecting appropriate methods, algorithms and tech stacks, and finally deployment and evaluation in production. Full Stack Data Science Full stack refers to the software engineer who is familiar with both the user-facing side and the backend infrastructure of software. Similarly, the full stack data scientist understands the analytics methods as well as user interaction and infrastructure needed to put it all into practice – a fitting description of my typical role in data science projects. I am especially interested in establishing software engineering best practices in the field of data science. Pragmatic AI Artificial Intelligence is currently both overhyped and underrated. We have seen some remarkable progress in AI capabilities, yet many companies struggle to put intelligent systems to work on everyday use cases. Work with me to go beyond the hype and connect business cases to technology – because many valuable, pragmatic cases for self-learning systems are within reach for your enterprise.

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AI Prompt Engineer and Python Programmer

I'm an entry-level Python programmer and AI engineer who's incredibly passionate about what I do. My brother suggested I'd excel in this field, and while I was skeptical at first, once I started tinkering with AI models, it was like the sky had opened up and my head finally cleared. I didn't have to puzzle it all out by myself anymore. Hooked immediately and wanting to do more, I completed the AI Engineering Bootcamp on Udemy, taught by the brilliant minds of Michael Taylor and James Phoenix. My Python studies were moving at a snail's pace until I discovered the magic of AI. It helped me break down complex code, interpret it, and do more with it in the last 12 days than I have been able to do in the last 12 months. But I'm not just an Engineer. I've been creating Art since I was 5, and not just macaroni pictures. With a background in digital and fine art, I bring a unique perspective to the table. My in-depth knowledge of art history and techniques helps me collaborate with AI image-generating models in a way that brings out the best in both worlds. I take those hazy ideas and add an artistic twist, so the AI creates exactly what we're envisioning. My ultimate goal has always been to become a game developer, and with AI, the resources I need to do that have been cut down to a fraction of the size. I truly believe it's one of the most powerful tools in the gaming realm, and I can't wait to dive in and craft some impactful experiences. If you're on the lookout for a Python programmer and AI Prompt engineer who's enthusiastic and loves merging technology with creativity, send me a message. If you want to check out the work I have made, both with and without AI, check out my Website and Artstation respectively, linked on my profile.

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