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. 💼💻As a Machine Learning Engineer, you’ll report directly to the co-founders and collaborate with a dynamic team. Your primary focus will be on developing and refining our AI embedding platform, ensuring it supports cutting-edge applications for structured data representation.
Responsibilities:

• Algorithm Development: Design, evaluate, and optimize machine learning models, especially for structured data (e.g., GNNs, Transformers), ensuring their efficiency and integration into our platform. 🧠
• Model Lifecycle Management: Oversee model integration, versioning, and maintenance within the platform infrastructure.
• Performance Monitoring: Track live model performance, develop debugging tools, and address issues swiftly. 📈
• Scalability & Reproducibility: Implement systems to ensure all experiments are scalable, reproducible, and traceable.
• Research & Innovation: Stay abreast of the latest advancements in GNNs and other ML techniques, integrating new approaches to enhance platform capabilities. 📚
• Collaboration: Partner with researchers and engineers to develop solutions that align with industrial and academic needs. 🤝

What We’re Looking For:

• Ph.D. or M.S. in Computer Science, Machine Learning, or a related field, with a focus on deep learning or representation learning.
• 3+ years of experience deploying, fine-tuning, and evaluating ML models (GNNs, Transformers).
• Expertise in Python and ML frameworks (e.g., PyTorch, JAX); familiarity with C/C++, Docker, and Kubernetes is a bonus!
• Strong knowledge of structured data systems (e.g., SQL, NoSQL, Parquet) for efficient data management. 💾
• Proven ability to thrive in a fast-paced, evolving startup environment. ⚡
• Excellent communication skills in English, with experience working across interdisciplinary teams.

Bonus Points:

• Publication record in top-tier ML conferences or journals.
• Demonstrated success in designing and running large-scale ML experiments.
• Open-source contributions or achievements in data science competitions.
• Proven track record of translating research into impactful business solutions.