Our client is a large and innovative educational organization that is building a next-generation digital learning ecosystem. The product includes a modern learning management system (LMS) and a companion mobile app used by thousands of students, parents, and teachers.
The platform supports personalized learning paths, real-time communication, automated attendance tracking, interactive course materials, assessments, and parental access.
The client is now launching a complete rebuild of the system from scratch to improve scalability, performance, user experience, and to expand functionality across web and mobile. Upcoming development also includes AI-driven features for personalized learning support.
If you enjoy building impactful products, leading engineering teams, and contributing to the future of EdTech — this role is an excellent match.
- Design, develop, and deploy machine learning models to power personalization,
recommendations, learner analytics, and adaptive learning paths - Analyze large-scale learner behavior data to extract insights and improve learning outcomes
- Build models for use cases such as:
* Content and course recommendations
* Learner skill inference and knowledge tracing
* Predictive analytics (engagement, completion, drop-off risk)
* Assessment scoring and feedback automation - Collaborate closely with product managers, engineers, and instructional designers to translate learning goals into AI solutions
- Develop and maintain data pipelines, feature engineering workflows, and model evaluation frameworks
- Experiment with and integrate LLMs and NLP techniques for content generation, feedback, and learner support
- Monitor model performance, bias, and drift in production and iterate for continuous improvement
- Document models, assumptions, and results to ensure transparency and reproducibility
- Strong experience with Python and common ML libraries (e.g., scikit-learn, PyTorch)
- Solid understanding of:
* Supervised and unsupervised learning
* Feature engineering and model evaluation
* Statistical analysis and experimentation (A/B testing) - Experience working with structured and unstructured data
- Proficiency in SQL and working with large dataset
- Ability to communicate complex technical concepts to non-technical stakeholders
- English level Upper Intermediate
Will be a plus:
- Experience building ML systems in ed-tech, LMS, or learning analytics domains
- Familiarity with LLMs, NLP, recommendation systems, or knowledge graphs
- Experience deploying models to production (APIs, batch pipelines, or real-time inference)
- Exposure to cloud platforms (AWS, GCP, Azure)
- Understanding of learning science, instructional design, or assessment theory
- Experience with MLOps tools (model versioning, monitoring, CI/CD for ML)
- 20 working days of paid vacation per year;
- Official holidays of Ukraine – days off;
- Modern equipment for work;
- Corporate events;
- External and internal training: conferences, professional events, courses, TechTalks;
- English speaking club.
- HR interview
- Interview with Head of Delivery
- Customer technical interview