Company Description

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 28,200+ 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.

Job Description

Roles & Responsibilities :

Design and develop scalable machine learning models for predictive analytics, classification, and optimization tasks.

Work closely with data engineering teams to gather, clean, and transform large-scale data for model training and evaluation.

Conduct A/B testing and performance monitoring of deployed models.

Communicate complex model outcomes and business impact to stakeholders in a clear and concise manner.

Contribute to model lifecycle management, including retraining pipelines and MLOps best practices.
 

Qualifications

Educational qualification:

Master’s or PhD in Computer Science, Data Science, Mathematics, or related field.

BE/BTECH in computer Science

Experience :

< 2yrs industrial experience

Mandatory/requires Skills :
Core Technical Skills (Traditional + Modern AI)

Machine Learning & Statistical Analysis

Classical ML (regression, classification, clustering, time-series)

Ensemble methods, boosting, decision trees

Deep Learning

CNNs for image analysis, RNNs/LSTMs/Transformers for sequence/time-series data

Frameworks: TensorFlow, PyTorch

Programming Languages

Python (must-have), plus SQL

Familiarity with R or MATLAB is a plus in engineering contexts

Data Engineering

Handling large-scale data, ETL, pipeline design

Tools: Spark, Airflow, dbt, etc.

Visualization & Reporting

Python (Seaborn, Plotly), Tableau, Power BI

AI / GenAI / Agentic AI Skills

Generative AI (GenAI)

Experience with LLMs (e.g., GPT-4, Claude, LLaMA) and frameworks like LangChain or Haystack

Fine-tuning or prompt engineering for domain-specific tasks (e.g., maintenance logs, technical documents)

Use of GenAI for report generation, document summarization, and automated insights

Agentic AI Systems

Designing autonomous agents capable of multi-step reasoning and action (e.g., Auto-GPT, BabyAGI, CrewAI)

Chaining models and tools to solve engineering workflows (diagnosis, optimization, scheduling)

Using tools like LangGraph, ReAct, and OpenAI function-calling or tool-use APIs

AI Tool Integration

Building AI-powered tools (e.g., chatbots for field engineers, document QA systems)

Leveraging vector databases (e.g., FAISS, Pinecone) for retrieval-augmented generation (RAG)

Preferred Skills :

Sensor & IoT Data Analysis

Real-time data processing, anomaly detection, predictive maintenance

Simulation & Modeling

Integration with engineering simulation data, digital twins

Optimization & Control

Operations research, control systems, system dynamics, reinforcement learning for control tasks

Additional Information

Requirements:

Strong programming skills in Python, R, or Scala with proficiency in ML libraries (scikit-learn, XGBoost, TensorFlow, PyTorch).

Solid understanding of statistical modeling, data mining, and