GigaML

GigaML is Hiring Founding Engineers in Bengaluru! 🚀 We are looking for talented founding engineers with 1+ years of experience to join our team in Bengaluru! 🇮🇳 Referral Bonus: 💰 Refer someone who would be a great fit and earn a referral bonus of $10k (8L INR) if they get hired! Job Details: Role: Full Stack Engineer Tech Stack: Django, React Base Salary: 30L - 75L Equity: 0.20% - 0.75% Joining and relocation bonus: Negotiable As a founding engineer, you will work closely with our customers in India and make a significant impact on our product. To apply, send your resume to hiring@gigaml.com. The full job description is in the comments below. About GigaML: GigaML is an applied AI lab building end-to-end customer care agents. Co-founded by Varun Vummadi (Left Stanford PhD in AI) and Esha Manideep (IIT KGP'23 rank 3), we raised $3.7M in seed funding led by Nexus Venture Partners and are part of Y Combinator's S23 Batch. Garry Tan, CEO of Y Combinator, personally invested in us! 🚀Let's revolutionize customer support together! 🤝

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Hey folks! Big shoutout to Kyle Wiggers and the amazing team at TechCrunch for featuring GigaML. They really nailed what we’re all about, and we're super pumped! Now, here’s where it gets exciting for all of you out there in legal, healthcare, and other data-sensitive industries. At GigaML, we’re all about keeping your data under your control. Our thing? Helping you deploy large language models (LLMs) right on your own turf – be it on your on-prem systems or your virtual private cloud (VPC). There is no need to send your precious data over to third-party cloud LLMs. Why does this matter? You get all the AI power without any of the privacy headaches. Whether it's sensitive legal cases or confidential patient info, your data stays with you. Safe, secure, and private. Wanna see this in action? Check us out at chat.gigaml.com. And if you're thinking, "Hey, this could work for us," just hit us up at varun@gigaml.com. We’re here to make AI work for you in the safest way possible. Big thanks again to Kyle and TechCrunch – you guys rock! Together, we’re taking AI privacy to the next level. https://lnkd.in/gDgYp2dM

Thanks to Valentina Escudero and Hina Dixit got writing about us

GigaML (YC S23) has recently closed $3.6M in seed funding to help enterprises securely train and deploy on-premise large language models (LLMs). As companies continue to explore the use of AI and LLM-based solutions in different applications, they continually face data security and compliance hurdles. As a result, open-source models are gaining traction as businesses turn to them for enterprise use. Founded by Varun Vummadi and Esha Manideep, Giga ML aims to be the solution for enterprises to customize and deploy Large Language Models in a secure way. It enables businesses to deploy LLMs as robust as GPT-4 directly on their own servers—so they don't have to send sensitive information to external servers like those of OpenAI. Giga ML's X1 Large 32k model, an advanced version of the llama2 70B 4k model, outperforms competitors like Mosaic ML and Together AI in fine-tuning capabilities. Sectors like healthcare, legal, and finance are keen on leveraging these models for customer support, internal knowledge searches, and code generation to boost engineering productivity. Congrats to the team on the round!

GigaML has raised $3.6 Mn in a seed funding round led by Nexus Venture Partners. Y Combinator, Liquid 2 Ventures, 8vdx and prominent angels like Garry Tan (Y Combinator president & CEO), also participated in the round. Founded 3 months ago by Varun Vummadi and Esha Manideep, GigaML helps enterprises secure on-premise deployment of Large Language models (LLMs). Enterprises can take Giga ML's base model and further continue pre-training and fine-tune it to meet their specific needs. #ai #fundraising

We are excited to announce our seed round to help enterprises build LLMs as powerful as GPT4.

We are thrilled to introduce X1 Large 32k, most powerful model deployable on-prem, brought to you by Giga ML in collaboration with Mano AI (YC S23). It's a finetuned version of Llama-2-70b with an extended context length of 32,768 tokens. X1 Large 32k is tailored for building industry specific LLMs such as finance, healthcare, legal and many more. With X1 Large 32k at the helm, enjoy the advantage of continuing pretraining, adept fine-tuning and RAG on petabytes of data, all bundled in a state-of-the-art on-premise solution. We've embedded advanced techniques to amplify its quality, versatility, and efficiency. Topping the charts, it scored an 8.1 on MT Bench, a leap from the 8.06 of Claude 2 and a significant advancement from the Llama 2 70B base model. Read more and experience X1 Large 32k at: https://lnkd.in/gHVFgskd. Contact us at founders@gigaml.com to make your on-premise model a reality within a week. #b2b #enterprise #generativeai #saas