Middle ML 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

If you’re excited about shaping the future of education and meet the qualifications listed above, we’d love to hear from you. Apply now to join Algonova!