Bosch Global Software Technologies Private Limited is a 100% owned subsidiary of Robert Bosch GmbH, one of the world's leading global supplier of technology and services, offering end-to-end Engineering, IT and Business Solutions. With over 27,000+ associates, it’s the largest software development center of Bosch, outside Germany, indicating that it is the Technology Powerhouse of Bosch in India with a global footprint and presence in the US, Europe and the Asia Pacific region.

Roles & Responsibilities :

About the Role

We are seeking an experienced Machine Learning Computer Vision Engineer to design and develop advanced computer vision algorithms for the Robocam V1.0 system. This role requires hands-on expertise in edge-based AI model deployment, embedded ML frameworks, and optimizing computer vision solutions for real-time and low-power environments.

Key Responsibilities

Design and develop computer vision algorithms for the Robocam V1.0 system.

Implement edge-based object and person detection solutions using onboard processing (with no cloud dependency).

Work with machine learning frameworks for embedded systems such as TensorFlow Lite or PyTorch Mobile.

Apply image processing and feature-extraction techniques relevant to surveillance and field monitoring use cases.

Integrate AI/ML models into embedded camera firmware, ensuring efficient deployment and low-power operation.

Collaborate with hardware and software teams to achieve optimal performance in embedded vision systems.

Test, debug, and optimize algorithms for real-world deployment conditions.

Educational qualification:

B.Tech

Experience : 5-7

Mandatory/requires Skills :
Required Skills & Experience

5–7 years of hands-on experience in computer vision and machine learning.

Strong knowledge of embedded AI frameworks (TensorFlow Lite, PyTorch Mobile, or similar).

Experience in object detection, person recognition, and real-time image analysis.

Proficiency in image processing, feature extraction, and edge-based deployment techniques.

Ability to work with embedded camera systems and optimize for low-power, resource-constrained environments.

Strong problem-solving and debugging skills.

Good to Have

Experience with C++/Python for ML model development and deployment.

Knowledge of hardware acceleration techniques (GPU, TPU, or NPU optimization).

Familiarity with surveillance systems and IoT-based vision solutions.