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.
is a joint venture between and , in partnership with , , and .
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:
- 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.
(Remote must be within 4-5 hours of CET timezone)
