If you're passionate about AI model design, embedding platforms, and innovation, this could be a fantastic fit! 🚀

They are a fast-growing AI startup, with ample runway, developing tools that help companies transform structured databases into powerful AI applications. They are combining state-of-the-art research with practical business solutions to revolutionize the AI industry. 💼💻

The Role: You’ll report to the co-founders and work alongside a close-knit engineering team, to improve their AI embedding models for structured data. Your responsibilities will include:

• Algorithm Development: Building and refining ML models for structured data representation 🧠
• Performance Optimization: Evaluating models and metrics to enhance their scalability and accuracy 📈
• Active Learning: Implementing strategies to improve training datasets and future model performance 🎯
• Collaboration: Engaging with industrial and academic partners to ensure their solutions meet diverse needs 🤝
• Research & Innovation: Keeping up with the latest AI advancements 📚
• Client Interaction: Ensuring client satisfaction through tailored solutions and easily adaptable pre-trained models 💼

You’ll also be part of their active learning initiatives, optimizing data selection, and working on foundational model analysis to ensure robust, scalable AI-driven solutions.

What They're Looking For:

• PhD or M.S. in Computer Science, Machine Learning, or a related field with a focus on deep learning or representation learning.
• MUST HAVE: Experience with Graph Neural Networks/Diffusion Models/Transformers, more Preferably GNN's 
• 3+ years of experience working on ML models (training, fine-tuning, and evaluating algorithms like GNN, Transformers) 🧠
• Ideally attain research background in relevant fields or published papers on relevant topics 📚
• Expertise in Python, PyTorch, and machine learning frameworks—experience with C/C++, Docker, and Kubernetes is a bonus!
• Strong knowledge of data structures and database systems (SQL, NoSQL, Parquet) for managing large datasets efficiently. 💾
• A problem-solving mindset with the ability to innovate and explore new ideas.
• Comfortable working in a fast-paced startup environment ⚡

Bonus points if you have a publication record in top-tier ML conferences or hands-on experience with large-scale ML experiments. Demonstrated contributions to open-source projects or success in data science competitions are also highly valued!