This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description This internship at Quansight is an opportunity to contribute to a PyData open source project, with dedicated mentorship from a project maintainer or contributor and interacting with the whole Quansight team. - Work on a challenging topic that will have significant value to the open-source community. - Potential projects include: - Working on NumPy, SciPy, Jupyter, conda-forge, stdlib.js, Polars, Narwhals, data-apis.org, and more. - Building a realistic performance benchmarking suite for a package. - Improving interoperability between two projects. - New feature development. - Creating a design system for accessible data visualization. - Implementing a new website design. - Refine skills such as: - Contributing to open source. - Pair programming. - Conducting effective code reviews. - Communication and collaboration. - Time management. - Work under the guidance of experienced mentors. - Network with other interns and the larger Quansight team. Qualifications - Good working knowledge of Python and Git is necessary. - Previous experience contributing to an open-source project is helpful but optional. - Familiarity with design tools such as Figma or Penpot is preferred for design-related internships. Requirements - Flexible start date: mid-June to mid-July. - Duration: 3 months. - Time commitment: 30-40 hrs/week. - English language proficiency: ability to communicate in written and oral English. - This program is open to current and non-students, including career changers, returners after a break in the workforce, boot camp alumni, self-taught developers/designers, etc. Benefits - This is a paid internship - the stipend is $1,500 per month for 40 hrs/week. - Competitive compensation. - Comprehensive sick policy and parental leave. - Generous amount of flexible paid time off. - Comprehensive benefits package for applicants located in the United States, Canada, Germany, or the UK. Application Process - Submit your application by the 9th of March 2026. - Include your CV and a one-page cover letter detailing specific projects, motivations, and interests in open-source software. - If applicable, share a link to your portfolio, GitHub profile, blog, or other resources. - Interview process includes: - First interview focusing on getting to know you and your passions. - Technical interview without code challenges, focusing on a walkthrough of your code or relevant projects. - Results communicated within 2-3 weeks after interviews. Commitment to Diversity, Equity, Inclusion, and Belonging Quansight values diverse creative practices and forms of knowledge, encouraging applications from all equity-seeking communities. We are an equal opportunity employer and do not discriminate based on various characteristics.

This description is a summary of our understanding of the job description. Click on 'Apply' button to find out more. Role Description We are hiring experienced NLP & Audio Analytics Trainers to deliver live online training sessions with hands-on labs and real-world projects for working professionals. - Conduct live, instructor-led online classes - Deliver coding demos, assisted practices, and projects - Address learner queries and ensure engagement Qualifications - 10+ years of hands-on experience in NLP and/or Audio Analytics - Strong Python and ML/DL skills - Prior online/classroom training experience Requirements - Natural Language Processing - NLP fundamentals, tools, and libraries (NLTK) - Text preprocessing, feature engineering, and visualization - Text vectorization: One-Hot, BoW, TF-IDF - Sentiment analysis using Naive Bayes - Word embeddings: Word2Vec, GloVe - Machine Translation and document search (TF-IDF, BM25) - Sequence models (RNNs) and challenges - Attention models, Transformers, BERT, GPT - Audio Analytics & Speech - Audio processing using Python (Librosa, PyDub) - Audio visualization and feature extraction - Digital Signal Processing and MFCCs - Deep Learning for speech recognition - Transfer learning for speech models - Audio synthesis and music generation using GANs Compensation The expected compensation for this role for candidates from the United States is $50 - $55 per hour for candidates who fulfill the qualifications for the role. Candidates whose qualifications are above those listed are encouraged to apply as well. All final offers to candidates will be based on that candidate's unique experience and skillset, and not all candidates will qualify for the top of the salary range.

• Conduct live, instructor-led online classes • Deliver coding demos, assisted practices, and projects • Address learner queries and ensure engagement

• 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