About
This is Aniket. Computer Engineering graduate with hands-on experience in software development and coding assessments through a 6-month internship as a Technical Content Engineer at HackerEarth. Skilled in developing and analyzing web-based applications, writing efficient code, and designing scalable solutions. Core Technical Skills: Proficient in Java, C++, Python, JavaScript, HTML, CSS, and SQL, with experience in frameworks such as Laravel, Django, and React. Strong understanding of data structures, algorithms, RESTful APIs, and database design. Passionate about writing clean, maintainable code and building user-centric web applications. AI & Emerging Technologies: Actively expanding skills in Artificial Intelligence, Machine Learning, and Data Analytics to stay aligned with the evolving needs of software engineering. Familiar with model development, data preprocessing, and predictive analytics using TensorFlow, scikit-learn, and Pandas. Exploring applications of AI-driven automation, natural language processing (NLP), and intelligent web systems to create smarter, more adaptive software solutions. I have a strong interest in full-stack development, algorithms, and system design, and I enjoy turning ideas into reliable, user-focused software. My internship experience gave me a solid understanding of developer workflows, coding standards, and scalable solution design. Now seeking opportunities to contribute as a Software Engineer or any similar roles where I can apply my technical foundation, embrace AI-driven innovation, and grow through challenging projects that push the boundaries of modern software development.
Work experience
Consultant at LTM, Feb 2026 - Present · 5 mos
Graduate Engineer Trainee at LTM, Nov 2025 - Feb 2026 · 4 mos
Technical Content Engineer Intern at HackerEarth, Jan 2025 - Jul 2025 · 7 mos, Remote, • Owned and authored 100+ programming problems across varied difficulty levels. • Designed and maintained 1,000+ questions across multiple formats including coding, full-stack projects, ML/DS case studies, and MCQs, driving large-scale learning engagement
