Senior Data Scientist (AI/ML)
bengaluru , India
Bosch Group
Moving stories and inspiring interviews. Experience the meaning of "invented for life" by Bosch completely new. Visit our international website.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 :
6+ 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)
Ethical & Responsible AI
Understanding AI safety, bias mitigation, explainability (e.g., SHAP, LIME)
Compliance with AI governance frameworks (e.g., ISO 42001, NIST AI RMF)
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
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
Tags: A/B testing AI governance Airflow APIs Chatbots Classification Claude Clustering Computer Science Data analysis Data Mining dbt Deep Learning Engineering ETL FAISS Generative AI GPT GPT-4 Haystack Industrial LangChain LLaMA LLMs Machine Learning Mathematics Matlab ML models MLOps Model training OpenAI PhD Pinecone Pipelines Plotly Power BI Predictive Maintenance Prompt engineering Python PyTorch R RAG React Reinforcement Learning Research Responsible AI Scala Scikit-learn Seaborn Spark SQL Statistical modeling Statistics Tableau TensorFlow Testing Transformers XGBoost
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