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 :

• Coordinate and consult the design, development, and deployment of AI and machine learning models across varied problem statements.

• Own the end-to-end AI model lifecycle — data exploration, feature engineering, model selection, training, validation, testing, and deployment.

• Build and maintain robust AI pipelines for continuous integration, retraining, and scalability of models.

• Develop APIs, microservices, or frameworks for embedding AI models into production applications.

• Conduct model performance benchmarking and implement optimization techniques for accuracy, latency, and efficiency.

• Research and implement state-of-the-art AI algorithms and architectures to enhance solution performance and adaptability.

• Collaborate with data scientists and product teams to align models with real-world business use cases.

• Ensure traceability, explainability, and compliance in all AI models developed.

• Mentor junior AI developers, review code, and contribute to establishing AI development best practices.

• Stay current with emerging trends in AI, MLOps, and generative AI tools to guide continuous innovation.

Required Skills & Qualifications

• Any Bachelor’s or Master’s degree

• 3–6 years of hands-on experience in AI model development, deployment, and optimization.

• Strong command of Python and libraries

• Deep understanding of machine learning algorithms, model training workflows, and deep learning architectures (CNN, RNN, Transformers).

• Experience with data wrangling, preprocessing, and feature engineering for model readiness.

• Skilled in developing and integrating models via APIs (Flask, FastAPI) and containerization using Docker.

• Proficiency in model evaluation metrics, hyperparameter tuning, and performance analysis.

• Experience with Git and collaborative code development workflows.

• Strong analytical mindset and ability to troubleshoot complex model behaviors.

   

   

Preferred Qualifications:

• Experience working with Large Language Models (LLMs), Generative AI, or prompt engineering

• Familiarity with cloud AI platforms

• Knowledge of MLOps practices — CI/CD for ML, model monitoring, and retraining pipelines.

• Exposure to computer vision or NLP-based AI systems.