Simulation Engineer - Industrial AI Solutions at Bosch in Bengaluru, India

Bosch is seeking a Simulation Engineer to join their Industrial AI Solutions team in Bengaluru, India. This role focuses on developing and deploying advanced Industrial AI and Process Twin solutions. The ideal candidate will leverage a strong foundation in data science, statistical modeling, machine learning, and simulation techniques, combined with a deep understanding of industrial processes.

Key Responsibilities:

Model Development & Validation

• Develop, train, and validate machine learning models (regression, classification, time series) based on project requirements and hypotheses.
• Build and calibrate simulation models for industrial processes, equipment, and systems.
• Utilize data analytics to extract insights from large datasets for optimization opportunities.
• Integrate domain knowledge and physics-based principles into data-driven models for enhanced accuracy and robustness.
• Perform statistical analysis, create visualizations, and communicate findings to stakeholders.
• Document models, algorithms, and code thoroughly.
• Stay current with advancements in AI, ML, and simulation techniques.
• Explore new technologies to address industrial challenges.

ML Engineering & MLOps

• Implement MLOps best practices for model deployment, monitoring, and maintenance.
• Automate model training, validation, and deployment pipelines.
• Collaborate with IT and DevOps teams for production deployments.
• Monitor model performance and retrain as necessary to maintain accuracy.

Edge Analytics & Deployment

• Develop and deploy lightweight AI models for edge computing environments.
• Design and implement data pipelines for edge data collection and processing.
• Integrate models with edge systems in collaboration with hardware engineers.

Collaboration & Communication

• Work with domain experts, program managers, and other data professionals to understand and solve business problems.
• Communicate complex technical concepts clearly to non-technical audiences.
• Participate in code reviews and knowledge sharing.
• Contribute to the development of data science and AI best practices and standards.

Qualifications:

Educational Qualification

Master's degree in Computer Science, Data Science, Engineering (Chemical, Mechanical, Electrical, Industrial), Statistics, or a related quantitative field.

Experience

• 5-8 years of experience in data science, machine learning, or simulation modeling, with demonstrated success in the industrial domain.
• Proven experience in developing and deploying AI models in production environments.
• Experience with edge computing and deploying models on edge devices is advantageous.

Mandatory Skills

• Strong programming skills in Python, R, or similar languages.
• Proficiency with machine learning libraries such as TensorFlow, PyTorch, scikit-learn.
• Experience with data analytics platforms and tools (e.g., Tableau, Power BI, SQL, NoSQL).
• Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP).
• Understanding of MLOps principles and tools (e.g., Kubeflow, MLflow).
• Mandatory understanding of industrial operations in at least one of the following sectors: Manufacturing, Steel, Oil & Gas, Energy, Mining, Chemicals, Textile, Pharma.
• Ability to translate domain expertise into data-driven models and simulation scenarios.

Preferred Skills

• Excellent communication, problem-solving, and analytical abilities.
• Ability to work effectively both independently and as part of a team.
• Strong organizational and time management skills.

This role offers the opportunity to drive performance improvements and optimization for clients by developing and deploying cutting-edge Industrial AI and Process Twin solutions.