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Develop and deliver software features and services across the SDLC, with emphasis on reliability, scalability, observability, and operational health. Responsibilities include writing and reviewing code, building microservices and distributed systems, supporting cloud deployments and CI/CD, participating in incident response and on-call rotations, troubleshooting issues, and collaborating with senior engineers and stakeholders.

Supports HR operations including attendance management, employee relations, onboarding, engagement programs, documentation, internal collaboration, and company activities. The intern also assists with HR visualizations, infographics, presentations, and ad hoc People Operations tasks while developing practical experience in a data-driven AI company.

Build and support data pipelines by manipulating data, implementing ETL processes, integrating big data tools, monitoring performance, and supporting software and data system development. Collaborate on AI and machine learning use cases involving structured and unstructured data while gaining hands-on experience with Docker, Kubernetes, and cloud technologies.

Assist with manual and automated testing for web applications, APIs, and other systems. Design and execute functional, regression, integration, and end-to-end test cases; develop automated scripts with Pytest and Playwright; perform API testing and data validation; document bugs; and collaborate with QA engineers and developers. Gain exposure to CI/CD, AI-assisted testing, and modern QA practices.

Analyze and clean data, build and evaluate machine learning and deep learning models, experiment with LLMs, agentic AI, forecasting, or computer vision, document results, communicate recommendations, and collaborate with data science teams on practical AI solutions.

Supports business development and pre-sales activities in the Data and AI industry. Responsibilities include market, competitor, and customer research; preparing proposals, presentations, pitch decks, demos, and proofs of concept; attending client meetings; collaborating with technical teams; and assisting with business analysis and reporting.

Develop client relationships and guide data and AI opportunities from discovery through signed engagement. Responsibilities include facilitating workshops, gathering requirements, developing business cases and ROI analyses, conducting market research, supporting proposals and presentations, translating business needs for technical teams, prioritizing POC/MVP features, managing the opportunity pipeline, and identifying account expansion opportunities.

As an AI/Machine Learning Engineer Intern, you will support deployment of AI models, develop scalable infrastructure, and write production-grade software. Work with senior engineers on generative AI projects and contribute to clear technical documentation.