<aside> ℹ️ About Kin We believe that Personal AI will be the most valuable digital asset that everyone will own. It cannot be kept in walled gardens. It must transcend ecosystems. And it must ultimately be owned and controlled by its user.‍ Kin is your AI companion for personalized support with long-term memory & privacy-by-design. With every conversation, Kin learns about your world to help coach you through situations over time and provide context on your past interactions

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The Role

We're on the lookout for a Machine Learning Engineer to enhance Kin's conversational AI capabilities. This role is crucial in building and refining the technological backbone that allows Kin to serve as a truly personalized AI companion. You'll be diving into large language models and conversational AI, ensuring Kin's interactions are as natural and effective as possible. You will develop and scale solutions that require large resources with high quality and low-latency SLAs.

Responsibilities

• Promote the transition from closed-source LLM APIs to open-source LLMs, optimizing, evaluating, deploying, and monitoring performance.
• Implement an advanced ML/LLM Ops workflow that concentrates on creating streamlined models for edge computing and improving software engineering productivity.
• Develop and optimize conversational AI models, focusing on large language models (LLMs).
• Spearhead initiatives aimed at improving the performance of language models within our primary offering.
• Stay informed and communicate the latest developments in AI.
• Work alongside our diverse team to effortlessly incorporate AI technology into Kin's platform, advancing AI developments for an improved user experience.

Requirements

• Commitment to Kin's ethos and principles, coupled with an enthusiasm for innovating within the Personal AI sector.
• Collaborative and proactive work ethic, with a willingness to define and own the roadmap alongside senior architects, PMs, and team leadership.
• Proficiency and professional experience in evaluating, fine-tuning, and deploying LLMs in production environments.
• Comprehensive experience in the field of software engineering, showcasing robust coding proficiency and a profound curiosity for Large Language Models.
• Proficiency in NLP, with experience in PyTorch, TensorFlow, HuggingFace, transformers, and Python.
• Proficient in English communication, adept at clearly conveying technical intricacies and the overarching product goals.
• A self-motivated and independent style, suited for a rapidly evolving startup atmosphere.

Welcomed addition

• Experience with Large Language Models, BERT, Embeddings, and similar technologies.