Machine Learning (Explainable AI)

microTECH Global LTD; Helsinki; On-site; EUR 70,000 - 110,000; Full time

Job summary

microTECH Global LTD is seeking a passionate researcher to advance AI and Safety across production-ready systems. Responsibilities focus on interpretability, alignment with human values, and robust model explanations.

The role requires strong publication records and collaboration in multidisciplinary teams. Candidate will explore novel methods in AI alignment, robustness, and explainability, with an emphasis on scaling techniques from research to production environments.

Qualifications

• Ph.D. in Computer Science, Deep Learning, ML, Mathematics or related field.
• Research focus in AI with strong motivation in Explainable AI and Safety domain.
• Proficient with Large Language Models, neural networks, and computer vision architectures.

Responsibilities

• Create new techniques to improve AI interpretability, bias reduction, transparency and alignment with human values for real-world scenarios.
• Ensure alignment between user explanations and intrinsic model behavior.
• Reverse-engineer neural networks to understand internal workings rather than treating them as black boxes.
• Develop data attribution methods to quantify influence of data points on predictions.
• Implement and integrate AI explainability techniques and tools.
• Build rigorous benchmarks and datasets to measure explanations, transparency, and treatment effectiveness.
• Communicate insights to stakeholders.

Skills

Interpretable AI

Explainable AI

LLMs

Neural networks

Computer vision

Python

Java

C++

PyTorch

TensorFlow

AI alignment

Model robustness

Continual learning

Education

PhD in CS/ML/Math

Tools

PyTorch

TensorFlow

Job description

We are looking for a passionate and motivated researcher with a solid track record of solving challenging problems, advancing state-of-the-art, and demonstrated passion for ground-breaking research that could be scaled to production environment with an emphasis on the intersection of AI and Safety.

Your responsibilities

• :· Create new techniques to make AI models more interpretable, unbiased, transparent and aligned with human values for real-world scenarios
• .· Create new techniques to ensure consistent alignment between user-centric explanations and intrinsic model behavior
• .· Reverse-engineer on neural networks to understand internal workings of AI models rather than treating them as "black boxes"
• .· Develop data attribution methods to quantify the influence of specific data points (text and image) on a model's prediction and implement solution
• .· Implement and integrate AI explainbility techniques and tools
• .· Build rigorous benchmarks and datasets to measure the quality of explanations, model transparency, and effectiveness of treatments
• .· Communicate insights to stakeholders

Requirement

• s:· Ph.D. in Computer Science, Deep Learning, Machine Learning, Mathematics or other related field
• s.· Focused on research in the AI field with good track records and high motivation in Explainable AI and Safety domai
• n.· Strong proficiency in Large Language Models (LLMs), neural networks, and computer vision architecture
• s.· Strong background in Python, Java, or C++, with deep knowledge of ML frameworks such as PyTorch, TensorFlo
• w.· Successful experience in AI alignment to human values and expectations, model robustness improvement, controlled and continual learning, neural network interpretability and editing techniques is highly value
• d.· Pioneering novel methods and neural networks that revolutionized machine learning or the AI field, or revolutionized the industry, is a big bonu
• s.· Strong publication record in top conferences (i.e. NeurIPS/ICLR/ICML/ AAAI/ACL/CVPR/ICCV/EMNLP/NAACL
• ).· Candidates with ICPC, IOI/IMO, IOAI and other international competition in computer science, machine learning, and AI, etc. are highly preferre
• d.· Good teamwork, enjoy working with multi‑culture teams, passionate in challenging the status qu
• o.