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Tier-1 brand and metro Hyderabad increase applicant density, while ML/testing niche moderates competition.
On-device ML testing focus increases domain specificity, though Python and ML framework skills transfer across industries.
Explicit 1–2 years plus mandatory Python, ML frameworks, and Electron/testing skills raises filter strictness.
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Design, develop, and validate embedded and cloud-edge software and utility programs supporting machine learning execution on Qualcomm chips.
Enhance benchmarking and validation infrastructure for deep neural networks through software engineering and machine learning knowledge.
Collaborate with cross-functional teams including systems, hardware, architecture, and test engineers to deliver system-level software solutions.
Bachelor’s degree in Engineering, Information Systems, Computer Science, or related field.
1 to 2 years of relevant work experience in software development or test development.
Expertise in test case development, automation, execution, and issue troubleshooting; experience with Electron app testing on Windows, Linux, macOS.
Strong Python development skills, understanding of machine learning and deep learning workflows, plus experience with TensorFlow or PyTorch.
Experienced in software and test development with practical exposure to testing frameworks like Jasmine and Playwright for Electron JS applications.
Comfortable working on machine learning model deployment on heterogeneous compute environments with integration into benchmarking tools.
Able to operate effectively in cross-disciplinary engineering teams focusing on software and system-level ML solutions.