AI/ML Engineer

O projekcie: The role includes developing new AI approaches and solutions, experimenting with cutting-edge architectures and driving innovation across business use cases. Additionally, experience in data engineering and cloud platforms will be valuable in delivering scalable and high‑impact AI capabilities. Main responsibilities: Proven experience delivering AI / ML / GenAI projects in enterprise environments Demonstrated ability to lead or significantly contribute to project development Strong understanding of the Software Development Life Cycle (SDLC) Experience working in automotive and/or financial services environments is highly preferred Strong communication skills English: mandatory French or German: strong plus About Spyrosoft Spyrosoft is an authentic, cutting-edge software engineering company, established in 2016. In 2021 and 2022, we were among the fastest growing technology companies in Europe, according to the Financial Times. We were founded by a group of tech experts with established backgrounds in software engineering, who created an ‘engineer-to-engineer’ workplace, powered by enthusiasm, fairness and authentic relationships. Having a unique offering, which bridge the gap between technology and business, we specialise in technology solutions for industry 4.0, automotive, geospatial, healthcare & life sciences, employee experience & education and financial services industries. Wymagania: - Minimum 2 years of experience in Data Science and Machine Learning.- Knowledge of machine learning, deep learning, and Generative AI (GenAI) techniques.- Proficiency in Python programming language and frameworks like TensorFlow, PyTorch, Pandas or Scikit-Learn.- Understanding of Natural Language Processes (NLP) techniques such as tokenization, string comparison and embeddings.- Experience with cloud platforms such as Azure or AWS.- Good communication and interpersonal skills, with the ability to collaborate effectively with team.- Bachelor's or Master's degree in Computer Science, Engineering, or a related field.Nice to have:- Apply trusted AI practices to ensure fairness, transparency, and accountability in AI models and systems.- Utilize tools such as Docker, Kubernetes, and Git to build and manage AI pipelines.- Implement monitoring and logging tools to ensure AI model performance and reliability.- Familiar with API building using Flask, FastAPI or similar.