AI/ML Developer (Chemistry, Industry)

Spyrosoft is a software engineering company established in 2016, specializing in technology solutions for industry 4.0, automotive, geospatial, healthcare & life sciences, employee experience & education, and financial services industries. The role focuses on designing, building, and deploying AI-driven solutions primarily within the Chemistry and Industrial sectors, emphasizing hands-on development, experimentation, and productionization of machine learning systems.

• Degree in Computer Science, Engineering, or a related technical field
• Proficiency in Polish and English (spoken and written)
• Strong programming skills in Python and experience with ML/AI frameworks such as TensorFlow, PyTorch, and scikit-learn
• Hands-on experience building and deploying machine learning models in production environments
• Solid understanding of machine learning techniques including Generative AI, Computer vision, classification, and regression
• Experience working with time-series data and industrial datasets
• Familiarity with industrial systems including SCADA, MES, ERP, SAP, and IoT
• Experience with data processing, storage, and pipeline development
• Knowledge of MLOps practices including CI/CD for ML, model monitoring, and versioning
• Ability to write clean, maintainable, and well-documented code
• Strong problem-solving skills and ability to work independently on technical challenges
• Willingness to work closely with business teams to shape and refine AI use cases
• Strong communication skills and ability to collaborate effectively with business stakeholders

Nice to have:

• Experience in Chemistry or industrial/manufacturing domains
• Familiarity with cloud platforms such as AWS, Azure, and GCP
• Experience with real-time data processing and streaming systems
• Understanding of production environments and operational metrics in factories
• Experience supporting or participating in pre-sales activities such as technical input to proposals and solution discussions

• Design, develop, and deploy machine learning and AI solutions, including Generative AI, computer vision, and predictive models
• Build scalable data pipelines and integrate models into production environments
• Collaborate with data engineers and scientists to process and analyze large datasets, including industrial and time-series data
• Translate business requirements into technical implementations, focusing on robust and maintainable solutions
• Develop and optimize algorithms for real-world industrial use cases such as predictive maintenance, anomaly detection, and process optimization
• Work with industrial data sources such as SCADA, MES, ERP, SAP, and IoT systems
• Implement model monitoring, validation, and continuous improvement pipelines following MLOps practices
• Contribute to system architecture focusing on performance, scalability, and reliability
• Prototype and experiment with new AI approaches, rapidly iterating toward production-ready solutions
• Support integration of AI systems into existing client infrastructure and applications