Anand Kumar

CEO

Bangalore Urban, Karnataka, India4 yrs 10 mos experience

Most Likely To SwitchAI ML Practitioner

Key Highlights

Expert in OS internals and security.
Led OpenSSH hardening on z/OS UNIX.
Developed advanced robotics and IoT solutions.

Stackforce AI infers this person is a Cybersecurity and IoT specialist with a focus on embedded systems and machine learning.

Contact

Skills

Core Skills

SecurityPlatform IntegrationSystem UtilitiesEmbedded SystemsMachine LearningCloud ComputingData ScienceRobotics

Other Skills

CCPPShell ScriptingEmbedded LinuxComputer VisionPythonAWS LambdaIndustry 4.0Data AnalysisRobot Operating System (ROS)Mixed RealityROSLinux KernelSystem CallsSignal Handling

About

Systems engineer specializing in OS internals, security, and performance-critical software. At IBM, I lead the porting, hardening, and stabilization of OpenSSH and Sudo on z/OS UNIX, working deep in C/C++, POSIX APIs, sockets, and platform-specific security integrations (SMF, RACF, syslog). I’ve resolved complex build, linker, and runtime failures, mitigated security vulnerabilities, and debugged production issues such as high-CPU sshd loops in customer environments. Previously at Cradlewise, I worked on Embedded Linux and edge-AI systems on ARM — spanning video pipelines, system services, kernel/build tooling, and on-device ML optimization. I enjoy working close to the OS boundary, where correctness, performance, and security matter.

Experience

4 yrs 10 mos

Total Experience

1 yr 2 mos

Average Tenure

2 yrs 4 mos

Current Experience

Ibm

2 roles

Advisory System Development Engineer

Promoted

Nov 2025 – Present · 7 mos · India · Hybrid

Acted as technical owner for Sudo on z/OS UNIX, leading design discussions, HLD/LLD documentation, and cross-team coordination across global IBM labs.

Staff System Development Engineer

Feb 2024 – Nov 2025 · 1 yr 9 mos · India · Hybrid

IBM z/OS UNIX: OpenSSH hardening, Shell & Utilities fixes across sysplex environments.
OpenSSH on z/OS — security & platform integration
Removed/mitigated selected CVEs, enforced stronger cipher/KEX/HostKey policies, integrated LibreSSL; migrated to SHA-2 baselines.
Integrated z/OS platform features (SMF logging, RACF/USS nuances); authored hardening guides and runbooks.
Customer issue: reproduced and mitigated an sshd high-CPU spike (serverloop/sockets), added diagnostics and safeguards to improve stability.
Shell & Utilities (Unix)
Contributed fixes to su, readlink, and ps for sysplex/USS edge cases; improved error handling and regression coverage.

CCPPSecurityPlatform Integration

Cradlewise inc.

Software Engineer

Jul 2022 – Feb 2024 · 1 yr 7 mos · Bengaluru, Karnataka, India · Hybrid

Embedded and Computer Vision engineer for ARM-based IoT product: video pipeline, connectivity, test automation, secure provisioning, and on-device ML.
Video pipeline: Improved exposure/white-balance quality across lighting conditions by optimizing static libs and PID control in C/C++; cross-compiled and tuned for ARM devices.
Connectivity services: Built autonomous Linux systemd service for BLE advertising and Wi-Fi provisioning using BlueZ D-Bus (GATT) and NetworkManager; implemented in Python.
Built serverless jobs/APIs with AWS Lambda (Python) fronted by API Gateway, secured with IAM and monitored via CloudWatch logs/metrics/alarms.
Hardware validation suite: Implemented diagnostics for I2C/SPI, CPU/GPU, audio/video, Wi-Fi, and Bluetooth using Device Tree, Linux sysfs, and kernel APIs for IoT bring-up.
Streaming & calibration tools: Integrated GStreamer with TCP/UDP sockets to capture frames remotely; added OpenCV-based contour/blur scoring and a PyQt5 UI for camera calibration workflows.
Build & kernel: Maintained custom Buildroot; created selective Makefile rebuilds; resolved Linux kernel compilation compatibility issues for custom modules/code.
On-device ML optimization: Tuned large ML models for ARM (ARM NN, TFLite) to meet GPU/memory constraints and achieve reliable real-time execution.

Embedded LinuxComputer VisionEmbedded SystemsMachine Learning

Cad lab, iisc bangalore

Student Researcher

Dec 2021 – Jun 2022 · 6 mos · Bengaluru, Karnataka, India

Developed a multi-sensor data pipeline and machine learning model to predict tool wear in CNC turning environments.
Integrated sensors including Accelerometer, Acoustic Emission (AE), Thermocouple, and DAC for real-time monitoring of cutting conditions
Designed a two-stage machine learning pipeline:
A soft sensor model using LSTM for cutting force prediction (achieved 92% accuracy)
A final tool wear classifier using few-shot learning techniques (achieved 88% accuracy)
Applied dimensionality reduction, anomaly detection, and multi-modal feature fusion techniques
Integrated transformer-based few-shot learning models to achieve material-agnostic prediction capability across different workpiece compositions
Project aligned with Industry 4.0 goals for predictive maintenance and adaptive smart manufacturing systems.

Machine LearningIndustry 4.0Data Science

I3d lab, iisc bangalore

Student Researcher

Jun 2021 – Nov 2021 · 5 mos · Bangalore Urban, Karnataka, India

At I3D Lab, I focused on advancing robotic control systems through augmented reality, specifically using Microsoft HoloLens and ROS. My work involved creating gesture recognition technologies for intuitive human-robot interactions, which are crucial for industrial applications. I also built spatial mapping pipelines and established communication protocols, enhancing the overall functionality of robotic systems.

Robot Operating System (ROS)Mixed RealityRobotics