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Bosch Group

AI/ML Engineer_MS

telengana, India

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What you’ll work on

Full posting

  • Design and implement ML and GenAI solutions including RAG pipelines, LLM integrations, prompt engineering, and evaluation/guardrail frameworks.

  • Develop and deploy API-based AI applications using FastAPI, Flask, or Plotly Dash.

  • Build end-to-end ML pipelines: data ingestion, feature engineering, model training, validation, deployment, and monitoring.

From the employer’s posting
Key Responsibilities Design and implement ML and GenAI solutions including RAG pipelines, LLM integrations, prompt engineering, and evaluation/guardrail frameworks. Develop and deploy API-based AI applications using FastAPI, Flask, or Plotly Dash.
Design and implement ML and GenAI solutions including RAG pipelines, LLM integrations, prompt engineering, and evaluation/guardrail frameworks. Develop and deploy API-based AI applications using FastAPI, Flask, or Plotly Dash. Build end-to-end ML pipelines: data ingestion, feature engineering, model training, validation, deployment, and monitoring.
Develop and deploy API-based AI applications using FastAPI, Flask, or Plotly Dash. Build end-to-end ML pipelines: data ingestion, feature engineering, model training, validation, deployment, and monitoring. Work with cross-functional teams to translate business needs into AI-driven outcomes.

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Tools in this posting

  • sql
  • aws
  • azure
  • bigquery
  • databricks
  • looker
Source — Tool mentions in context
Job Description We are seeking an experienced AI/ML Engineer (4–6 years) with strong hands-on expertise in end-to-end machine learning, GenAI solution development, data engineering, and cloud-native deployment. The role involves building scalable AI systems, designing LLM-based applications, and integrating enterprise-grade MLOps pipelines across any one of Azure, GCP, and AWS environments. Key Responsibilities
- Design and implement ML and GenAI solutions including RAG pipelines, LLM integrations, prompt engineering, and evaluation/guardrail frameworks. - Develop and deploy API-based AI applications using FastAPI, Flask, or Plotly Dash. - Build end-to-end ML pipelines: data ingestion, feature engineering, model training, validation, deployment, and monitoring.
- Work with cross-functional teams to translate business needs into AI-driven outcomes. - Deploy workloads using Azure App Service, Cloud Run, Azure Bot Service, Dialogflow, and other cloud-native platforms. - Implement MLOps workflows for CI/CD, model registry, experiment tracking, and automated retraining.
- Implement MLOps workflows for CI/CD, model registry, experiment tracking, and automated retraining. - Build and optimize ETL/ELT pipelines using Azure Data Factory, BigQuery, Databricks, and other data engineering tools. - Create dashboards and analytical insights using Power BI, Tableau, Looker, QuickSight, or ThoughtSpot.
- Build and optimize ETL/ELT pipelines using Azure Data Factory, BigQuery, Databricks, and other data engineering tools. - Create dashboards and analytical insights using Power BI, Tableau, Looker, QuickSight, or ThoughtSpot. - Ensure scalable, secure, and cost-optimized deployment across Azure/GCP/AWS environments.
- Create dashboards and analytical insights using Power BI, Tableau, Looker, QuickSight, or ThoughtSpot. - Ensure scalable, secure, and cost-optimized deployment across Azure/GCP/AWS environments. Required Technical Skills
Programming & Languages - Python (advanced), SQL (strong), HTML/CSS/JavaScript (working knowledge) LLMs & GenAI
- LangChain, LangGraph - Google ADK, Vertex AI, AWS Bedrock - RAG architectures, embeddings, vector retrieval
- Prompt design, evaluation metrics, guardrails/security - Azure AI Foundry, Azure OpenAI, Azure AI Search, Azure Document Intelligence - Custom model development using GPT, LangChain, and relevant frameworks
Data Engineering & Platforms - BigQuery, Azure Synapse, Azure Data Factory, Databricks - Blob Storage, Cloud Storage, Document AI
BI & Analytics - Power BI, Tableau, Looker, ThoughtSpot, QuickSight DevOps & MLOps
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telengana, India

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Posting history
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First seen by us
Sep 7, 2026
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Last seen by us
Sep 8, 2026

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Skills in this posting

sqlawsazurebigquerydatabrickslookertableaufastapiflaskplotly

Job description

Job Description

Job Description

We are seeking an experienced AI/ML Engineer (4–6 years) with strong hands-on expertise in end-to-end machine learning, GenAI solution development, data engineering, and cloud-native deployment. The role involves building scalable AI systems, designing LLM-based applications, and integrating enterprise-grade MLOps pipelines across any one of Azure, GCP, and AWS environments.

Key Responsibilities

  • Design and implement ML and GenAI solutions including RAG pipelines, LLM integrations, prompt engineering, and evaluation/guardrail frameworks.

  • Develop and deploy API-based AI applications using FastAPI, Flask, or Plotly Dash.

  • Build end-to-end ML pipelines: data ingestion, feature engineering, model training, validation, deployment, and monitoring.

  • Work with cross-functional teams to translate business needs into AI-driven outcomes.

  • Deploy workloads using Azure App Service, Cloud Run, Azure Bot Service, Dialogflow, and other cloud-native platforms.

  • Implement MLOps workflows for CI/CD, model registry, experiment tracking, and automated retraining.

  • Build and optimize ETL/ELT pipelines using Azure Data Factory, BigQuery, Databricks, and other data engineering tools.

  • Create dashboards and analytical insights using Power BI, Tableau, Looker, QuickSight, or ThoughtSpot.

  • Ensure scalable, secure, and cost-optimized deployment across Azure/GCP/AWS environments.

Required Technical Skills

Programming & Languages

  • Python (advanced), SQL (strong), HTML/CSS/JavaScript (working knowledge)

LLMs & GenAI

  • LangChain, LangGraph

  • Google ADK, Vertex AI, AWS Bedrock

  • RAG architectures, embeddings, vector retrieval

  • Prompt design, evaluation metrics, guardrails/security

  • Azure AI Foundry, Azure OpenAI, Azure AI Search, Azure Document Intelligence

  • Custom model development using GPT, LangChain, and relevant frameworks

  • Prompt engineering, LogProbs handling, vector search integrations

Data Engineering & Platforms

  • BigQuery, Azure Synapse, Azure Data Factory, Databricks

  • Blob Storage, Cloud Storage, Document AI

  • Strong understanding of ETL/ELT, feature engineering & data profiling

  • Event-driven architecture and streaming systems for agentic workflows

  • Data ingestion, transformation, and vector database management

  • Ensuring data quality, lineage, governance, and observability

BI & Analytics

  • Power BI, Tableau, Looker, ThoughtSpot, QuickSight

DevOps & MLOps

  • Docker, CI/CD pipelines

  • Model deployment & monitoring

  • Vertex AI Agent Engine, model registry, experiment tracking

Qualifications

Educational qualification:

Bachelor’s/Master’s degree in Computer Science, Engineering, or related field.

Experience :

4–6 Years

 

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 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.