Develop, train and evaluate machine learning models and translate analytical insights into robust, reproducible ML workflows, collaborating closely with engineering teams to bring both classical ML and Generative AI models into production Design and implement Generative AI and LLM based solutions, including model selection, prompt design, structured evaluation, and responsible operation aligned to business needs Ensure production readiness and model quality by applying best practices in MLOps, deployment strategies, monitoring, model lifecycle management, as well as performance measurement, hallucination reduction and safety guardrails Build and refine AI agents capable of reasoning, taking actions, interacting with data sources, and orchestrating workflows Improve model performance through structured evaluation, quality measurement, hallucination reduction, and safety guardrails Apply best practices in identity, access control, data protection, and enterprise security policies Translate complex AI concepts into clear, actionable content for technical and non technical audiences Work closely with business stakeholders, domain experts, architects, and software engineers to integrate AI into real processes Training & Support Create best practices, enablement materials, and usage guidelines for Generative AI Serve as a trusted advisor for internal teams adopting AI Technologies Bachelor's degree in Information Technology, Data Management, Business Intelligence, or a related field Experience in Data Science with a strong foundation in classical data science and machine learning as well as motivation to work on production ready AI systems and openness to applying Generative AI technologies as part of their work Strong background in classical data science and machine learning, including exploratory data analysis, feature engineering, statistical modeling, and quantitative model Evaluation Hands-on experience in developing, training and evaluating ML models such as time series analysis and forecasting, anomaly detection, image or signal classification, or similar applied ML Problems Hands-on experience building AI agents using LLMs.
Experience with Microsoft Copilot Studio or Microsoft 365 integrations beneficial Proficiency in Python and ability to write clean, maintainable, well-structured code Knowledge of cloud platforms, preferably Azure (compute, security, networking, identity, and AI related services) Strong communication skills and ability to work with stakeholders Innovation driven and proactive in exploring new ideas and approaches Familiarity with production environments and best practices in MLOps, such as deployment strategies, monitoring, model lifecycle management, reproducibility and quality assurance Job description: Build Generative AI Solutions: Develop, train and evaluate machine learning models and translate analytical insights into robust, reproducible ML workflows, collaborating closely with engineering teams to bring both classical ML and Generative AI models into production Design and implement Generative AI and LLM based solutions, including model selection, prompt design, structured evaluation, and responsible operation aligned to business needs Ensure production readiness and model quality by applying best practices in MLOps, deployment strategies, monitoring, model lifecycle management, as well as performance measurement, hallucination reduction and safety guardrails Build and refine AI agents capable of reasoning, taking actions, interacting with data sources, and orchestrating workflows Improve model performance through structured evaluation, quality measurement, hallucination reduction, and safety guardrails Apply best practices in identity, access control, data protection, and enterprise security policies Collaboration & Documentation: Translate complex AI concepts into clear, actionable content for technical and non technical audiences Work closely with business stakeholders, domain experts, architects, and software engineers to integrate AI into real processes Training & Support Create best practices, enablement materials, and usage guidelines for Generative AI Serve as a trusted advisor for internal teams adopting AI Technologies Profile description: Bachelor's degree in Information Technology, Data Management, Business Intelligence, or a related field Experience in Data Science with a strong foundation in classical data science and machine learning as well as motivation to work on production ready AI systems and openness to applying Generative AI technologies as part of their work Strong background in classical data science and machine learning, including exploratory data analysis, feature engineering, statistical modeling, and quantitative model Evaluation Hands-on experience in developing, training and evaluating ML models such as time series analysis and forecasting, anomaly detection, image or signal classification, or similar applied ML Problems Hands-on experience building AI agents using LLMs.
Experience with Microsoft Copilot Studio or Microsoft 365 integrations beneficial Proficiency in Python and ability to write clean, maintainable, well-structured code Knowledge of cloud platforms, preferably Azure (compute, security, networking, identity, and AI related services) Strong communication skills and ability to work with stakeholders Innovation driven and proactive in exploring new ideas and approaches Familiarity with production environments and best practices in MLOps, such as deployment strategies, monitoring, model lifecycle management, reproducibility and quality assurance We offer: Flexible working hours Training opportunities & structured onboarding and development planning Opportunity for coaching, mentoring and networking ams OSRAM is an Equal Employment Opportunity Employer.
Diversity, equity and inclusion is strongly established in our corporate culture and we firmly believe it makes us more successful as a company.
All qualified applications will receive consideration for employment regardless of ethnic, national or social origin, gender, gender identity, sexual orientation, color, religion, age, physical and mental abilities.
Daria Berezova ****** #J-*****-Ljbffr