Internship Overview
We are seeking a highly analytical Software Engineer Intern to evaluate, validate, and optimize complex software algorithms across production systems. This role focuses on ensuring algorithmic correctness, numerical accuracy, scalability, and optimal performance using both theoretical analysis and real-world benchmarking.
The Logic Auditor plays a critical role in preventing performance regressions and guaranteeing that deployed logic meets strict efficiency and reliability standards.
Additional Information of the Intern
| Company | Smarttrak Ai Technologies Private Limited |
| Location | Hyderabad |
| Internship Duration | 6 months |
| Salary | ₹ 15,000 /Month |
| Working Days | 5 Days |
| Internship Type | Work From Home |
| Qualification | Bachelor’s degree |
| Skill | Proficiency in Python for scripting, testing, and automation |
| Knowledge | In-depth knowledge of algorithms: Sorting, Searching, Shortest Path, Traversals |
Key Responsibilities
– Design automated benchmarking frameworks to measure time and space complexity across varying dataset sizes and edge cases
– Evaluate algorithm behavior under real-world and worst-case scenarios
– Implement unit tests and formal validation methods to verify correctness across all valid input permutations
– Ensure logical consistency and deterministic outcomes
– Identify CPU and memory bottlenecks using profiling tools
– Recommend and validate optimizations to improve runtime efficiency
– Perform asymptotic analysis to assess algorithmic complexity before implementation
– Review proposed logic for scalability and computational feasibility
– Build controlled A/B testing frameworks to compare algorithmic approaches
– Evaluate trade-offs between strategies such as Greedy, Dynamic Programming, and Graph-based methods
– Embed algorithm validation and performance checks into CI/CD pipelines
– Prevent performance regressions in new releases through automated audits
Required Skills & Qualifications
– Strong command of data structures: Trees, Graphs, Heaps, Hash Maps
– In-depth knowledge of algorithms: Sorting, Searching, Shortest Path, Traversals
– Proficiency in Python for scripting, testing, and automation
– Strong C++ skills for performance-critical analysis and profiling
– Solid understanding of Discrete Mathematics
– Knowledge of Probability and Linear Algebra
– Experience with automated testing frameworks such as PyTest, Google Test, or equivalent
– Familiarity with Docker and CI/CD tools like Jenkins or GitHub Actions
– Experience automating performance benchmarks in deployment workflows
– Hands-on experience with CPU and memory profiling tools (e.g., cProfile, Valgrind, similar)
