Data Scientist + Associate Instructor - AI/ML

About:

Key Responsibilities:

• Teach Applied AI/ML: Design and deliver practical, project-based courses in AI/ML (e.g., Python for ML, Statistics, ML Algorithms, Deep Learning, NLP, CV, ML Ops, GenAI).
• Develop Industry-Relevant Curriculum: Help design and update the AI/ML curriculum to reflect current industry tools, techniques, and best practices, incorporating your own professional experience and case studies.
• Mentor Student Projects: Guide students through hands-on AI/ML projects, providing technical direction, code reviews, and feedback based on industry standards.
• Guide & Mentor Students: Advise students on developing practical skills, understanding career paths in AI/ML, and preparing for internships and job placements.
• Stay Current: Keep your expertise sharp on the latest AI/ML trends and technologies, bringing that knowledge into the classroom.
• Collaborate: Work closely with other industry-expert faculty and staff to create a unified and effective learning experience.
• Assess Practical Skills: Create and evaluate assignments, projects, and assessments focused on measuring practical application and understanding.

Required Qualifications & Experience:

• Bachelor's or Master's degree in Computer Science, Engineering, Data Science, AI/ML, or a similar field. (A PhD is valued but not required.)
• Minimum 4-8 years of direct, hands-on professional experience in the tech industry as an AI/ML Engineer, Data Scientist, Research Scientist, or similar role involving significant AI/ML development and deployment.
• Proven Industry Track Record: Demonstrable experience building, training, and deploying machine learning models (including deep learning) to solve real-world problems.
• Deep AI/ML Understanding: Strong grasp of core ML algorithms (classical & deep learning - CNNs, RNNs, Transformers), underlying theory, model evaluation, statistics, and current research/industry trends.
• Passion for Teaching/Mentoring: Clear ability and enthusiasm for explaining complex technical topics and guiding others. Experience in corporate training, mentoring junior team members, leading workshops, creating technical content, or supervising projects is highly relevant. (Formal academic teaching experience is not a prerequisite.)

Required

• Proficiency with data science libraries (Pandas, NumPy, Scikit-learn).
• Hands-on experience with ML/DL frameworks (TensorFlow, PyTorch).
• Strong SQL and data handling skills.
• Understanding of ML Ops practices and tools (Git, Docker, Cloud platforms -
• AWS/GCP/Azure).
• Knowledge of key AI areas (NLP, Computer Vision, Generative AI/LLMs).
• Communication: Excellent ability to explain technical concepts clearly to students.
• Strong mentoring skills.
• Collaboration: Team-oriented approach.
• Passion: Genuine interest in education and student success within an innovative,
• practical learning environment. 

Good-to-Have:

● Prior teaching experience at the undergraduate or graduate level.

● Familiarity with modern teaching methodologies and academic tools.

Perks & Benefits

● Competitive salary packages aligned with industry standards.

● Access to state-of-the-art labs and classroom facilities.

● Contribution to cutting-edge academic work in collaboration with the Newton School of Technology and Rishihood University.