
Senior AI Scientist
- España
- Permanente
- Tiempo completo
- New features: 50-70%
- Documentation: 15%
- Meetings, incl. supervision: 10-30%
- Maintenance: 5%
- Depending on current needs, the role may be responsible for:
- Leading significant parts of work in the lifecycle of development of learning educational capabilities
- Research & development in the field of creating data-driven educational products and solutions
- Designing, implementing and maintaining learning capabilities based on machine-learning and statistics, in collaboration with Engineering teams
- Designing frameworks for monitoring capabilities performance on production (in collaboration with Engineering teams); evaluating results for improvement
- Creating and conducting internal trainings
- Creating technical documentation, incl. patent documentation
- Sharing work results internally and externally (publications, conferences, meetups)
- Staying up to date with state-of-the-art methods in the scope of own specialisation, e.g. NLP, speech processing, statistical modelling, psychometrics
- Providing input into team vision, goals, and processes
- Leading, mentoring and coaching a small group of direct reports (from intern to regular level data scientists)
- Supervising or leading colleagues with less experience
- Experience with generative AI models and techniques.
- Strong collaboration with engineering teams to develop and implement AI solutions.
- Proven experience in building production-ready machine learning models to solve diverse set of business problems.
- Good knowledge of statistical modelling and machine learning theory
- Strong proficiency in Python and machine learning frameworks, e.g. pandas, numpy, scikit-learn, NLTK, spaCy, Hugging Face, TensorFlow, PyTorch
- Strong hands-on experience in using state-of-the-art methods in the scope of own specialisation, e.g. NLP, speech processing, statistical modelling, psychometrics, reinforcement learning
- Proficiency in SQL and relational databases
- Ability to translate business needs into research problems
- Ability to apply best practices for machine learning and software engineering
- Experience with Git-based code review
- Proficiency in Linux, Unix or macOS
- Some experience in working with non-technical stakeholder
- At least intermediate presentation and mentoring skills
- Ability to work in a diverse, remote, asynchronous team
- Collaboration skills, e.g. being able to give (and receive) feedback
- Proficiency in written and spoken English and a key local language
- Familiarity / experience with:
- MLOps and DevOps
- Docker and Kubernetes
- cloud infrastructure, preferably AWS, Azure
- cloud data processing, e.g. Snowflake or AWS Redshift
- distributed data processing, e.g. Spark