Data Scientist / AI & Machine Learning Specialist

Integrify is an upskilling and recruitment services provider that brings IT professionals and tech teams together. Over 150 organizations, including ABB, Telia, TietoEvry, Digia, and Fujitsu, trust the expertise of our professionals.

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We are now seeking an experienced Data Scientist / AI/ML Specialist to join one of our partner companies' R&D teams. 

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Are you the tech expert ready to take the next step in your career and tackle new challenges in cutting-edge AI development?

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About the Role

We are looking for an experienced Data Scientist / AI&ML Specialist to join an in-house R&D team. You will be instrumental in developing intelligent, world-class services that move beyond proof-of-concept and directly into robust, commercial-ready applications.

This role requires a balance of deep scientific rigor and practical engineering skill. You will focus on building robust, scalable AI systems that solve complex, real-world problems.What you'll be doing 

• Architecting & Developing: Design, develop, and optimize cutting-edge deep learning architectures for complex structured or image-based data.
• Driving Innovation: Apply state-of-the-art AI/ML methods (e.g., transfer learning, multimodal learning, generative models) to dramatically improve solution accuracy, reliability, and scalability.
• Ensuring Robustness: Integrate uncertainty quantification techniques into model predictions to guarantee performance and dependability in critical production environments.
• Collaboration: Work closely with product managers and engineering teams to align model development with tangible, practical use cases.
• MLOps & Deployment: Contribute to robust model deployment pipelines, ensuring reproducibility and high reliability in real-world, production settings.
• Documentation: Clearly document methods and results for both highly technical and non-technical stakeholders.

What you'll need to succeed 

• Deep Learning Expertise: Strong theoretical foundation and professional, practical experience with deep learning methods applied to image or structured data.
• Python Power: Advanced Python programming skills with expertise in modern frameworks like PyTorch and/or TensorFlow.
• Production Experience: Proven hands-on experience moving AI/ML solutions from research/PoC phases into robust production systems.
• Reliability Knowledge: Knowledge of uncertainty quantification techniques; familiarity with Bayesian approaches is a significant advantage.
• Engineering Mindset: Solid familiarity with modern software engineering practices, including Git, CI/CD, containerization (e.g., Docker), and cloud environments.

Bonus points if you have 

• Experience in specialized data analysis within complex domains (e.g., medical imaging, geospatial, finance).
• Understanding of industry-specific data standards (e.g., DICOM, HL7, FHIR, or similar specialized data protocols).
• Excellent communication and collaboration skills—the ability to bridge technical, clinical, and business perspectives.
• An advanced degree (PhD/MSc) in Computer Science, Data Science, Applied Mathematics, or a related field.