AI Scientist
At a glance
Mid-level AI Research role at Qutwo. Helsinki.
Pay not stated AI Research salary
aimlroles summary, based on the employer's posting.
What you'll do
- Investigate AI questions and put the findings into ML solutions that address customer needs
- Develop models through the full machine-learning process, from initial work to practical deployment
- Represent complicated business workflows as reliable mathematical models
- Coordinate with scientists, engineers and customers, while providing academic guidance to fellow scientists
What you bring
- At least three years of relevant work after a PhD, or equivalent tenure, on foundational AI and ML challenges
- A record of influential research, including first-author work at leading conferences, or high-performance scalable ML implementation
- Practical involvement across the end-to-end machine-learning model development process
- You use first-principles reasoning, adjust to changing conditions and communicate across different disciplines
Who this fits
This full-time role suits someone who pairs research with practical ML development and works closely with customers and internal teams. Mentoring scientists is part of the work. NLP and LLMs, recommender systems, ML in listed sectors, and quantum computing are helpful areas of experience.
From the employer
Join Qutwo - Europe's private Quantum AI Lab, on our quest to bridge the gap between the classical and the quantum world. We partner with the most advanced and forward-thinking customers, solving fundamental real-world problems, side by side.
We are seeking Exceptional AI Scientists. If you are a humble learner, not afraid of the unknown, we encourage you to apply. You will join our team in a full-time capacity, collaborating closely with our scientists, engineers, and customers. In this role, you will apply a blend of exploratory research and practical implementation to drive customer value through ML solutions.
Requirements
A strong track record of high-quality, high-impact research, marked by deep contributions to the field and first-author publications at top-tier venues (e.g., NeurIPS, ICML, ICLR, CVPR), and/or proven experience in implementing high-performance, scalable ML solutions.
Minimum of 3 years of relevant post-PhD experience (or equivalent tenure) solving complex, ambiguous, and foundational problems in AI and ML.
Problem-solving skills rooted in first principles, paired with the readiness to adapt to a dynamic environment and the ability to translate complex business processes into robust mathematical models.
Some practical experience in full-stack model development, encompassing the end-to-end Machine Learning pipeline.
Ability to work collaboratively and communicate effectively across disciplines, both internally and externally.
Ability to mentor scientists through rigorous academic guidance.
Experience in one or more of the following areas is a plus but not a requirement:
NLP and LLM, including work with large or small models and fine-tuning.
Recommender systems.
Experience applying ML within the Financial, Pharmaceutical, AI Safety and Security, Logistics and other Services sector.
Knowledge of quantum computing.