Responsibilities
- Translate product requirements to AI problems and identify areas where AI can drive the most business impact
- Analyze data to uncover significant patterns and generate actionable insights
- Architect agentic and GenAI systems
- Select appropriate models for the right tasks and tune their performance
- Perform exploratory data analysis (EDA) and feature engineering to support the modeling process
- Apply best practices on model selection, parameter tuning etc.
- Run comparative experiments for model training
- Analyze ML metrics to evaluate different potential solutions
- Manage the full lifecycle of AI features, from data collection to model design and to implementation and optimization in production
- Mentor and guide junior members, sharing knowledge and leading complex projects
Requirements
- Hands on experience with GenAI and Agentic applications
- Extensive hands-on experience in delivering AI driven products to production
- Experience in scaling and optimisation of AI applications
- Knowledge of machine learning algorithm and respective theory
- Knowledge of the Python machine learning ecosystem and solid software background in OOP
- Strong skills in teamwork, communication, and analytical thinking
- Fluency in English, both oral and written
Nice to Have
- Experience with Big Data tools (Spark/PySpark) and cloud environment, ideally Azure / Databricks
- Previous experience in LLM fineturing
- Previous experience with LLM serving
- Knowledge of Deep learning
Additional Information
- Fluency in English, both oral and written
