Job Description & How to Apply Below
With a diverse membership comprising data scientists, researchers, educators, and
industry experts, ADaSci fosters a vibrant community that drives innovation and
pushes the boundaries of data-driven insights. Through conferences, workshops,
and online resources, ADaSci empowers its members with the latest advancements,
best practices, and emerging trends in data science, enabling them to thrive in an
ever-evolving landscape. ADaSci offers invaluable opportunities for professionals to
connect, grow, and make a meaningful impact in the world of data science.
We are seeking a highly skilled and experienced Freelance AI & ML Instructor to
deliver comprehensive corporate training sessions to experienced professionals. The
ideal candidate will have deep expertise in artificial intelligence (AI), machine
learning (ML), cloud platforms (Azure, AWS, GCP), data engineering, and MLOps.
Responsibilities:
Develop and deliver engaging and informative training sessions on AI, ML, and related topics to experienced professionals.
Design and implement hands-on labs and practical exercises that reinforce learning objectives.
Customize training materials to align with the specific needs and backgrounds of corporate clients.
Provide real-world examples and case studies to illustrate key concepts and best practices.
Evaluate and assess participants' understanding and progress through interactive activities and assessments.
Stay up-to-date with the latest trends, tools, and technologies in AI, ML, cloud computing, data engineering, and MLOps to ensure the relevance and accuracy of training content.
Offer insights and guidance on best practices for deploying and managing ML models in production environments.
Facilitate discussions and answer participants' questions to enhance their learning experience.
Qualifications:
Graduate with 10+ years of experience, postgraduate with 5+ years of experience, PhD with 2+ years of experience
Proven experience as an instructor or trainer in AI, ML, data engineering, or related fields.
Deep knowledge of AI and ML algorithms, techniques, and frameworks.
Proficiency in at least one major cloud platform (Azure, AWS, GCP).
Experience with MLOps, including ML model deployment, monitoring, and lifecycle management.
Strong understanding of data engineering principles and best practices.
Familiarity with scalable, reliable system design and architecture.
Excellent communication and presentation skills, with the ability to convey complex concepts in an accessible manner.
Strong problem-solving skills and the ability to adapt training content to meet the needs of diverse audiences.
Preferred
Skills:
Hands-on experience with AI/ML frameworks (e.g., Tensor Flow, PyTorch, scikit-learn).
Knowledge of containerization technologies such as Docker.
Experience with big data technologies (e.g., Hadoop, Spark).
Previous experience in corporate training or educational settings.
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