Middle AI Engineer

We are looking for a Middle ML Engineer to help us build and refine the core of our adaptive mathematics course. You will work on real-world production systems that personalize education for kids in real-time. This is a role for a builder who loves writing code, running experiments, and seeing their models impact hundreds of thousands of users.

Your Goals:

• Feature Implementation: Develop and integrate AI-driven features that help the math curriculum adapt to student performance.

• Scalable Execution: Help transition ML prototypes into reliable production services that handle global traffic.

• Agent Development: Build and fine-tune LLM-based agents and RAG components to solve specific educational challenges.

• Continuous Improvement: Speed up the experiment cycle by improving data pipelines and evaluation scripts.

👾 Your Job:

• LLM Integration: Implement and debug orchestration logic, memory management, and guardrails for our AI agents.

• RAG & Search: Support and optimize retrieval systems, ensuring high-quality context for our LLM chains.

• Dataset Engineering: Prepare high-quality custom datasets for fine-tuning and build automated evaluation (Eval) pipelines.

• Production Support: Monitor ML services in production, identifying and fixing latency issues, drifts, or performance degradations.

• Collaborative Building: Work closely with senior engineers and product managers to turn pedagogical requirements into technical reality.

💜 Requirements:

• Engineer-First Approach: Solid Python skills and experience writing production-ready code (not just notebooks).

• ML Foundations: Practical experience with LLMs, RAG patterns, and vector databases.

• Framework Proficiency: Comfort with PyTorch/TensorFlow and modern LLM frameworks (LangChain, LlamaIndex, or similar).

• Production Mindset: Experience (or strong desire to learn) deploying and monitoring services in a cloud environment.

• Proactive Learner: A high degree of autonomy and the ability to dive deep into new technologies to solve a problem.

• English B2: Able to read technical documentation and communicate clearly with an international team.

Would be an advantage:

• EdTech & Psychometrics: Experience with knowledge tracing (IRT/BKT/DKT), error diagnostics, and mastery models.

• Graph Technologies: Proficiency in Knowledge Graphs, graph databases (e.g., Neo4j), and graph algorithms.

• Model Optimization: Hands-on experience with on-device/self-hosted models and inference optimization.

🦄 What We Offer:

• AI-Centric Impact: Join a product-led team where ML is the core priority, giving you direct influence over the architecture and roadmap.

• Autonomy & Speed: Work with high autonomy in a flexible environment with rapid feedback loops from real-world users.

• Competitive salary and benefits package

• Fully remote and flexible work options