Assistant Manager - Learning Designer

Job Description

Job Title: Assistant Manager - Learning designer (AI/ML) Location: HSR, Bangalore (Work from office) Experience Required: Minimum 4 years Department: Product Innovation Employment Type: Full-time Role Overview: We are looking for a passionate AI/ML Subject Matter Expert with a strong background in Artificial Intelligence, Machine Learning, Python, and Deep Learning to support our course development initiatives. As an SME, you will collaborate with the content, instructional design, and product teams to create high-quality, industry-relevant learning content. Key Responsibilities: Research and stay updated on emerging trends, tools, and technologies in AI/ML, Python, Deep Learning, and Data Science. Contribute to designing, reviewing, and refining Simplilearns AI/ML curriculum and learning paths. Create and validate course content including learning objectives, project ideas, assessments, and use cases. Work closely with instructional designers to ensure technical accuracy and pedagogical effectiveness. Support the content production team with scripting, reviewing, and storyboarding. Participate in webinars, doubt sessions, and learner engagement activities when required. Guide the integration of industry use-cases and capstone projects to enhance learner outcomes. Required Skills and Qualifications: Minimum 4 years of hands-on experience in AI/ML and related technologies. Proficiency in Python, with experience in libraries like NumPy, Pandas, Scikit-learn, TensorFlow, Keras, or PyTorch. Strong understanding of machine learning algorithms, data preprocessing, deep learning models, and NLP. Good analytical and communication skills. Experience in curriculum development or content creation is a strong plus. Exposure to e-learning, edtech, or training is desirable. Nice to Have: Published work, blogs, or GitHub projects in AI/ML. Experience with LLMs, GenAI, or RAG frameworks. Prior instructional design or teaching experience. Exposure in effectively lead and manage a team by allocating tasks based on individual strengths and capabilities to ensure optimal performance and successful project delivery.