Role & responsibilities Build Audio ML/DL models for given requirement Build models from scratch wherever required Must be able to code relevant research papers independently Tune to improve accuracy and latency Support to satisfy the deployment requirements of the product Apply transfer learning wherever required Training, fine tuning and optimization of different flavors of transformer models Hands on experience with LLM, fine tuning and Optimization of LLM Audio AI Modelling and tuning experience Audio AI concepts, ML/DL working experience in Pytorch/Tensorflow/Keras framework Variations of CNN, RNN, Attention Mechanism, Transformers and large models like wav2vec, whisper Proficiency in machine learning/audio pre-processing libraries/frameworks such as Librosa, Kaldi, sklearn, python speech features, Numpy, Scipy, Pandas, Matplotlib. Signal Processing fundamentals, understanding the data characteristics and wave signals Transfer Learning Experience in Acoustic models for speech recognition systems. Experience in Voice activity detection with noise analysis & denoising Experience in WakeupWord, ASR Working experience of LLM fine tuning, optimization and performance improvement. Audio AI Audio related certification Tools for creating Synthetic data Experience working in Edge devices Experience in noise augmentation and mixing techniques

Role & responsibilities Proficiency in C/C++ programming Language and embedded System Development Experience in developing Board support package(BSPs) and Device driver for peripherals based on I2C, SPI, UART Knowledge of hardware platforms and system Architectures(ARM Arch, Vector table, Startup code, Boot loader Etc) Experience with debugging tools such as HW Debugger, Oscilloscope, Multi meter, Logical Analyzer. Knowledge in RTOS/FreeRTOS/ZephyRTOS/Linux

Role & responsibilities 7 to 8 years of hands-on experience in network engineering and migration. Proficiency in F5 technologies, particularly LTM and AWAF. Strong understanding of web protocols (HTTP/HTTPS, SSL/TLS) and application-layer security. Experience with WAF deployment and tuning for optimal protection. Familiarity with bot protection and DDoS mitigation strategies. Exposure to security analytics platforms such as SecureWorks is a plus. Excellent communication and interpersonal skills to work effectively in a collaborative environment. Preferred Qualifications: Relevant certifications such as F5 Certified Technology Specialist (F5-CTS), CISSP, or equivalent. Experience in cloud environments (AWS, Azure) is an added advantage.

Mode of Work : Office (Mandatory) Job Description: Expert in Dart & Flutter with a proven track record in production-grade app development Skilled in scalable architectures: Bloc, Provider, Riverpod, MVVM, Clean Architecture Deep native integration experience: Swift (iOS), Kotlin/Java (Android), Web, Windows Proficient in state management (Riverpod, Bloc, Provider) and RESTful API integration Strong testing skills: unit, widget, and integration tests (flutter_test, integration_test, Mockito) Experienced in app profiling: performance, memory, frame rendering, UI responsiveness Knowledge of app security best practices: secure storage, encryption, obfuscation Developed and maintained reusable Flutter packages/plugins (internal & open-source) Custom UI components and animations using Flutters rendering/animation systems Familiar with Flutter flavors: dev, staging, production CI/CD experience: GitHub Actions, Bitrise, automated testing & deployment Full app lifecycle ownership: architecture, development, release, monitoring, support Tools: Firebase Crashlytics, Firebase Analytics, Sentry for crash reporting and analytics Strong debugging and problem-solving skills in complex mobile systems Agile methodologies, Git version control, Jira, and Confluence experience