Responsibilities
- develop, test, and deploy GenAI, agentic, and ML models that address concrete business use cases
- work with cross-functional partners (product, data, and engineering) to design and integrate scalable AI capabilities into existing systems
- build and maintain pipelines for data preparation, experimentation, evaluation, and model monitoring
- contribute to prompt engineering, retrieval-augmented generation (RAG), and other modern NLP and LLM-based applications
- support the development of internal tools and reusable modules (e.g., reasoning agents, evaluation frameworks, feedback loops)
- apply best practices in MLOps, model validation, and responsible AI to ensure quality, transparency, and compliance
Requirements
- Master’s or PhD in Computer Science, Machine Learning, Data Science, or related field
- at least 5 years of experience applying ML/AI methods in enterprise or research environments and proven experience with GenAI or NLP applications (LLM fine-tuning, RAG, LangChain, or similar)
- strong programming skills in Python and experience with ML frameworks (PyTorch, TensorFlow, Scikit-learn, Hugging Face)
- ability to translate business needs into analytical or ML solutions with tangible impact
- strong communication and collaboration skills across technical and business teams
- working knowledge of data privacy, compliance, or governance considerations in regulated industries
Nice to Have
- familiarity with MLOps tools (CI/CD, model registry, vector databases, containerization)
- experience integrating AI models with production systems or APIs is an asset
