Snehal Reddy
Software Engineer III at Google
London, England, United Kingdom
Summary
👤
Senior🎓
Top SchoolSnehal Reddy is a Software Engineer III at Google based in London, bringing eight years of hands-on experience in low-level security firmware across kernel, hypervisor, and trusted execution environments. A pre-final year IIT Kharagpur undergraduate in Computer Science, Snehal blends academic excellence with production-grade systems work, from designing Pixel Secure Boot global config to building high-performance telemetry for TEEs. He now focuses on integrating Rust into Pixel’s Root-of-Trust in partnership with ARM and developing AI tooling for security software, demonstrating a rare mix of firmware security and modern language adoption. Past internships at Microsoft, Cambridge, and multiple startups, plus leadership of robotics and coding clubs, reflect strong applied research and team-building skills. Notably, Snehal has contributed to RF-A related trusted firmware efforts and maintains an active GitHub profile that complements his Google SWE persona. He’s drawn to hard systems challenges and consistently ships secure, performance-sensitive solutions at silicon bring-up cadence.
8 years of coding experience
5 years of employment as a software developer
Bachelor's degree, Computer Science, 9.11, Bachelor's degree, Computer Science, 9.11 at Indian Institute of Technology, Kharagpur
English, Hindi, Telugu
Stackoverflow
9reputation
3kreached
0answers
2questions
Github Skills (13)
code-coverage10
cover10
c-language10
cprogramming-language10
system-programming10
coverage10
debug9
memory-management9
debugging9
uuid8
facebook-graph-api6
pygame6
python6
Programming languages (5)
Github contributions (5)
Snehal-Reddy/Pygame-project
Dec 2017 - Oct 2020
Key stroke
Contributions:8 PRs, 29 pushes, 2 branches in 2 years 10 months
stroke
thebhatman/ML_RRT-_APF
Dec 2018 - Mar 2019
Rapidly exploring not so randomised trees imporvised with Artificial Potential Field and Machine Learning
Contributions:96 commits in 3 months
artificialmachine-learningfieldartificial-intelligencetrees
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