Senior Researcher: Explainable AI & Safety Innovator

microTECH Global Limited; Helsinki; Hybrid; EUR 70,000 - 110,000; Full time

Job summary

microTECH Global Limited in Helsinki seeks a passionate researcher with a solid track record of solving challenging problems, advancing state-of-the-art methods, and a demonstrated drive to scale ideas to production in the AI and Safety domain.

You will create techniques for interpretable, unbiased, and aligned models; reverse-engineer neural networks; develop data attribution methods; implement explainability tools; build benchmarks; and clearly communicate insights to stakeholders.

Qualifications

• PhD in CS/ML/Math or related field.
• Strong publication record in top venues (e.g., NeurIPS/ICLR/ICML/ AAAI/ACL...).
• Experience with LLMs, neural networks, and computer vision architectures.
• Proficiency in Python, Java, or C++, with ML frameworks (PyTorch, TensorFlow).
• Experience with AI alignment, model robustness, continual learning, interpretability and editing techniques.
• International competition experience valued.

Responsibilities

• Create new techniques to make AI models more interpretable, unbiased, transparent and aligned with human values for real-world scenarios.
• Create techniques to ensure alignment between explanations and model behavior.
• Reverse-engineer neural networks to understand internal workings.
• Develop data attribution methods to quantify influence of data points on predictions.
• Implement and integrate AI explainability tools and techniques.
• Build rigorous benchmarks and datasets to measure explanations and transparency.
• Communicate insights to stakeholders.

Skills

Explainable AI

AI safety focus

Research leadership

Education

PhD in Computer Science or related field

Tools

PyTorch

TensorFlow

CUDA

Job description

microTECH Global Limited in Helsinki seeks a passionate researcher with a solid track record of solving challenging problems, advancing state-of-the-art methods, and a demonstrated drive to scale ideas to production in the AI and Safety domain.

You will create techniques for interpretable, unbiased, and aligned models; reverse-engineer neural networks; develop data attribution methods; implement explainability tools; build benchmarks; and clearly communicate insights to stakeholders.