AI ML Expert IN 2026

Company Description

In India, Bosch is a leading supplier of technology and services in the areas of Mobility Solutions, Industrial Technology, Consumer Goods, and Energy and Building Technology. Additionally, Bosch has in India the largest development center outside Germany, for end to end engineering and technology solutions. The Bosch Group operates in India through twelve companies with a combined strength of over 31,500 associates which includes around 15,650 research and development associates.

Bosch Automotive Electronics India Pvt. Ltd. (RBAI) is a 100% subsidiary of Robert Bosch GmbH . Established in 2009, in Naganathapura - Bengaluru, RBAI is primarily focused in manufacturing electronic products for the automotive sector. RBAI has consistently added an average of one product every year resulting in a wide range of products comprising – Engine Control Units (ECU) for both 4W and 2W, Body Control Modules (BCM), ECUs for ABS, DC-DC Converters, iTraMS (Intelligent communication control unit) to name a few. RBAI also produces products for eMobility like MCU (Motor control Unit), C-Box (Communication Box), VCUs (Vehicle Control Unit), Central gateway modules and is geared up for other futuristic products. RBAI with its diverse portfolio, not only caters to local markets, but also exports products to all major global customers. The Naganathapura Plant (NhP1) is seen as a benchmark in Operational Excellence in AE and Bosch India , using an integrated approach of Bosch Production System (BPS) and I4.0. With a young and agile team, RBAI’s mission statement ‘Be RBAI’ (Be Reliable Benchmark Agile Innovative) is a testament to our commitment in providing best in class products and services for its customers.

Job Description

Key Responsibilities:

• Data Analysis and Preprocessing:

• Gather, clean, and preprocess structured and unstructured data for analysis.
• Perform exploratory data analysis (EDA) to uncover trends, patterns, and actionable insights.

• Model Development:

• Develop, train, and validate machine learning models to address business challenges.
• Implement deep learning algorithms where applicable for advanced analytics.

• Data Visualization:

• Create interactive dashboards and reports to visualize insights using tools like Tableau, Power BI, or Python libraries (e.g., Matplotlib, Seaborn, Plotly).
• Communicate results and recommendations effectively to stakeholders.

• System Integration and Deployment:

• Integrate ML models into production environments and ensure their scalability and performance.
• Use tools like TensorFlow Serving, Flask, FastAPI, or Docker for model deployment.