Machine Learning (ML)
Python
Kubernetes
DockerJob Overview:
As a Technical Lead, you will be responsible for leading the design, development, and deployment of AI-powered Edtech solutions. You will mentor a team of engineers, collaborate with data scientists, and work closely with product managers to build scalable and efficient AI systems. The ideal candidate should have 8-10 years of experience in software development, machine learning, AI use case development and product creation along with strong expertise in cloud-based architectures.
Key Responsibilities:
AI Tutor & Simulation Intelligence
- Architect the AI intelligence layer that drives contextual tutoring, retrieval-based reasoning, and fact-grounded explanations.
- Build RAG (retrieval-augmented generation) pipelines and integrate verified academic datasets from textbooks and internal course notes.
- Connect the AI Tutor with the Simulation Lab, enabling dynamic feedback — the system should read experiment results, interpret them, and explain why outcomes occur.
- Ensure AI responses remain transparent, syllabus-aligned, and pedagogically accurate.
Platform & System Architecture
- Lead the development of a modular, full-stack platform unifying courses, explainers, AI chat, and simulation windows in a single environment.
- Design microservice architectures with API bridges across content systems, AI inference, user data, and analytics.
- Drive performance, scalability, and platform stability — every millisecond and every click should feel seamless.
Reliability, Security & Analytics
- Establish system observability and monitoring pipelines (usage, engagement, AI accuracy).
- Build frameworks for ethical AI, ensuring transparency, privacy, and student safety.
- Set up real-time learning analytics to measure comprehension and identify concept gaps.
Leadership & Collaboration
- Mentor and elevate engineers across backend, ML, and front-end teams.
- Collaborate with the academic and product teams to translate physics pedagogy into engineering precision.
- Evaluate and integrate emerging tools — multi-modal AI, agent frameworks, explainable AI — into the product roadmap.
Qualifications & Skills:
- 8–10 years of experience in software engineering, ML systems, or scalable AI product builds.
- Proven success leading cross-functional AI/ML and full-stack teams through 0→1 and scale-up phases.
- Expertise in cloud architecture (AWS/GCP/Azure) and containerization (Docker, Kubernetes).
- Experience designing microservices and API ecosystems for high-concurrency platforms.
- Strong knowledge of LLM fine-tuning, RAG pipelines, and vector databases (Pinecone, Weaviate, etc.).
- Demonstrated ability to work with educational data, content pipelines, and real-time systems.
Bonus Skills (Nice to Have):
- Experience with multi-modal AI models (text, image, audio, video).
- Knowledge of AI safety, ethical AI, and explain ability techniques.
- Prior work in AI-powered automation tools or AI-driven SaaS products.
Shubham Vishwakarma
Full Stack Developer - Averlon
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Follow CutshortShubham Vishwakarma
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