Sr. Engineer - Computer Vision and Machine Learning

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.