Create a positive, professional and inclusive learning environment, by:
Teaching select lessons in accordance with learning objectives and fidelity to session plans provided by Simplilearn
Employing strategies known to meet the needs of adult learners, including leveraging tech tools, instructional best practices and connecting content to the real world by sharing industry insights and professional experiences
Managing regular communication with students to align on progress, expectations, celebrate milestones and address concern areas
Providing individualized student support during synchronous class sessions and outside class synchronously during office hours and asynchronously through timely communication
Evaluate student performance and progression toward competencies based on course deliverables and course rubrics, by:
Providing constructive and timely feedback to students in the cohort
Assisting in the management of Performance Action Plans for individual students who need additional support
Serve as role model for students and as an ambassador for our brand, by:
Exhibiting professionalism and an ethical and empathetic approach when engaging with Simplilearn staff, students, and the public
Promoting student retention and amplify student satisfaction by creating a positive classroom culture for the Learning Team, communicating timely with students and leveraging effective interventions and sharing of resources
Encouraging teamwork and seek feedback for continuous improvement

Requirements

5+ years of hands-on experience in Machine Learning (ML) and Deep Learning (DL), including developing and deploying models using Python, TensorFlow, PyTorch, or other ML frameworks
A deep understanding of machine learning algorithms and concepts, such as supervised and unsupervised learning, neural networks, support vector machines, decision trees, and reinforcement learning
Solid background in mathematical foundations of machine learning, including probability theory, linear algebra, optimization, and statistical analysis
Experience with the full ML lifecycle, from data pre-processing, feature engineering, and model selection, to model evaluation and deployment in real-world applications
Proficiency with the ML stack, including libraries like Pandas, NumPy, Scikit-learn, Keras, and working knowledge of big data tools such as Spark or Hadoop (optional but preferred)
Experience working with real-world data, including handling structured and unstructured datasets, data cleaning, and performing exploratory data analysis (EDA)
Previous teaching or mentoring experience, ideally in an online learning environment
A passion for teaching and the ability to simplify complex AI/ML topics to make them accessible to learners at various skill levels
Strong communication and presentation skills (verbal and written), with a focus on engaging and student-centric teaching methods
Professionalism, integrity, and empathy in all learner and team interactions.

Benefits

Compensation: The expected compensation for this role is $50 - $55 per hour for candidates who fulfill the qualifications listed.
Candidates with advanced qualifications or domain expertise are encouraged to apply as well.
All final offers will be determined based on individual experience, skillset, and alignment with the program needs.
Not all candidates will qualify for the top of the salary range.

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

Machine LearningDeep LearningPythonTensorFlowPyTorchmachine learning algorithmsneural networksdata pre-processingfeature engineeringmodel evaluation

Soft Skills

communication skillspresentation skillsteamworkempathyprofessionalismintegritystudent-centric teachingmentoringcontinuous improvementfeedback