Senior AI/Machine Learning Scientist

Full Job Description

Complexio is Foundational AI works to automate business activities by ingesting whole company data – both structured and unstructured – and making sense of it. Using proprietary models and algorithms Complexio forms a deep understanding of how humans are interacting and using it. Automation can then replicate and improve these actions independently.

Complexio  is a joint venture between Hafnia and Símbolo , in partnership with Marfin Management , C Transport Maritime , Trans Sea Transport  and BW Epic Kosan . 

About the job

As an AI/Machine Learning Scientist at Complexio, 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)