Senior AI/Machine Learning Scientist

At Quintessential AI, we’re not just building technology; we’re creating a super brain—a natural interface dubbed ‘q’—designed to redefine human interaction with machines. Our mission is to embed artificial intelligence deeply into business operations, utilizing a suite of diverse Large Language Models (LLMs) and sophisticated data-matching algorithms. These technologies are taught to autonomously align your data with recurring business processes, enriching them with context and sentiment analysis to enhance decision making and efficiency. This allows for a seamless partnership between humans and AI, where technology supports human creativity and ingenuity.

About the job

As an AI/Machine Learning Scientist at Quintessential, you will be responsible for designing, developing, and implementing machine learning models and algorithms that can automate business processes. You will work closely with cross-functional teams, including data engineers, software developers, and domain experts, to drive advancements in a range of technologies including Large Language Models, Process Mining and Graph Databases.

 Key Responsibilities

• Research, design, and implement machine learning models to solve business challenges.
• Work closely with software developers to integrate machine learning models into production systems.
• Stay abreast of the latest developments in AI and machine learning research to inform project strategies.
• Provide expertise and guidance on machine learning best practices to the broader team.
• Contribute to the development and maintenance of a scalable and robust AI infrastructure.

Requirements

Requirements:

• Ph.D. degree in Computer Science, Data Science, Machine Learning, or a related field.
• Experience in AI/Machine Learning research and development.
• Proficiency in Python.
• Experience with popular machine learning frameworks (TensorFlow, PyTorch, scikit-learn).
• Experience with using NVIDIA GPUs for fine tuning AI models
• Strong mathematical and statistical background.
• Excellent problem-solving and critical-thinking skills.

Preferred Qualifications

• Experience with deep learning techniques and architectures.
• Familiarity with natural language processing (NLP) and Large Language Models (LLMs).
• Knowledge of distributed computing and cloud platforms (AWS, Azure, or Google Cloud).
• Research experience in Graph Neural Networks would be a plus.
• Strong publication record in relevant conferences or journals.

Benefits

(Remote must be within 4-5 hours of CET timezone)