Machine Learning Engineer

Position Overview:

We are seeking a talented and experienced Machine Learning Engineer with a strong background in graph databases. The ideal candidate will be instrumental in developing and enhancing our knowledge bases and Retrieval-Augmented Generation (RAG) models, driving the accuracy and efficiency of our AI-powered solutions. You will play a key role in deploying cutting-edge models that enhance the AI features of our end-user applications, ensuring they meet the evolving needs of our customers.

Key Responsibilities:

• Design, build, and improve ML models, focusing on retraining and optimizing open-source models using Neo4j or similar graph databases.
• Deploy and continuously refine open-source models to enhance AI features within end-user applications, ensuring high performance and reliability.
• Keep abreast of the latest industry and academic research to integrate new technologies that enhance or replace existing solutions and products.
• Collaborate closely with Product Managers and customers to understand requirements and translate them into effective ML solutions that address real-world problems.

Minimum Qualifications:

• 2+ years of experience as a Machine Learning Engineer, Applied Scientist, or equivalent role, with a proven track record of developing and deploying ML models.
• Strong proficiency in Python and familiarity with common machine learning tools (e.g., Spark, PyTorch).
• Experience in deploying models and refining them based on iterative customer feedback.
• Demonstrated expertise in optimizing distributed model training processes, preferably with GPUs.
• A deep passion for Generative AI and Large Language Models (LLMs), with a keen interest in staying ahead of industry trends.
• Previous experience with graph databases, specifically Neo4j, and an understanding of their application in building knowledge bases and RAG models.

Desirable Skills

Experience with Databricks or similar platforms is considered a plus.
Excellent communication and collaboration skills, with the ability to work effectively in a team environment.
A problem-solving mindset, with a strong emphasis on creativity and innovation in approaching complex technical challenges.