AI Engineer - Thermo Fisher Scientific Oy - Remote - Global

As part of the Thermo Fisher Scientific team, you’ll discover meaningful work that makes a positive impact on a global scale. Join our colleagues in bringing our Mission to life every single day to enable our customers to make the world healthier, cleaner and safer. We provide our global teams with the resources needed to achieve individual career goals while helping to take science a step beyond by developing solutions for some of the world’s toughest challenges, like protecting the environment, making sure our food is safe or helping find cures for cancer. We are looking for an AI Engineer to join our growing AI Engineering team supporting Global Business Services (GBS) Digital Enablement. In this role, you will help design, develop, and implement AI-driven solutions that enhance operational efficiency across global finance and shared service teams. You will work closely with cross-functional stakeholders to identify opportunities, build prototypes, and support the adoption of AI and machine learning solutions across the organization. Build and test AI/ML models, systems and prototypes to solve business problems Support integration of AI solutions with existing systems and workflows Work with cross-functional teams to customize and configure third-party AI tools Participate in data preparation, analysis, and model evaluation Monitor and improve model performance and solution effectiveness Contribute to documentation, demos, and knowledge sharing to support adoption Stay updated with emerging AI trends and tools. Core qualifications include a Bachelor’s degree in Computer Science, Data Science, AI, or related field, 2-5 years of experience in AI, Machine Learning, or Data Science, understanding of AI/ML fundamentals, prompt engineering, embeddings, and RAG concepts, familiarity with LLMs such as OpenAI GPT, Claude, Gemini, or Llama, understanding of the AI/ML lifecycle, including training, evaluation, and monitoring, experience with Python, data processing, and version control tools (e.g., Git), familiarity with API integration concepts and RESTful services, strong analytical, problem-solving, and prototyping skills, good communication skills and ability to work with cross-functional teams. Nice to have skills include experience integrating AI/LLM APIs into applications or systems, familiarity with semantic search, vector embeddings, or AI workflows, experience with cloud platforms such as AWS, Azure, or GCP, familiarity with Docker, Kubernetes, or LLMOps tooling, experience with vector databases or RAG pipelines.