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Job Description
We are seeking an experienced AI/ML Engineer (5–8 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
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Design and implement ML and GenAI solutions including RAG pipelines, LLM integrations, prompt engineering, and evaluation/guardrail frameworks.
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Develop and deploy API-based AI applications using FastAPI, Flask, or Plotly Dash.
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Build end-to-end ML pipelines: data ingestion, feature engineering, model training, validation, deployment, and monitoring.
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Work with cross-functional teams to translate business needs into AI-driven outcomes.
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Deploy workloads using Azure App Service, Cloud Run, Azure Bot Service, Dialogflow, and other cloud-native platforms.
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Implement MLOps workflows for CI/CD, model registry, experiment tracking, and automated retraining.
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Build and optimize ETL/ELT pipelines using Azure Data Factory, BigQuery, Databricks, and other data engineering tools.
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Create dashboards and analytical insights using Power BI, Tableau, Looker, Quick Sight, or Thought Spot.
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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
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Lang Chain, Lang Graph
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Google ADK, Vertex AI, AWS Bedrock
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RAG architectures, embeddings, vector retrieval
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Prompt design, evaluation metrics, guardrails/security
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Azure AI Foundry, Azure OpenAI, Azure AI Search, Azure Document Intelligence
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Custom model development using GPT, Lang Chain, and relevant frameworks
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Prompt engineering, Log Probs handling, vector search integrations
Data Engineering & Platforms
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Big Query, Azure Synapse, Azure Data Factory, Databricks
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Blob Storage, Cloud Storage, Document AI
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Strong understanding of ETL/ELT, feature engineering & data profiling
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Event-driven architecture and streaming systems for agentic workflows
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Data ingestion, transformation, and vector database management
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Ensuring data quality, lineage, governance, and observability
BI & Analytics
- Power BI, Tableau, Looker, Thought Spot, Quick Sight
Dev
Ops & MLOps:
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Docker, CI/CD pipelines
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Model deployment & monitoring
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Vertex AI Agent Engine, model registry, experiment tracking
Educational qualification:
Bachelor’s/Master’s degree in Computer Science, Engineering, or related field.
Experience :
5–8 Years
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.
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About Bosch

Bosch
PublicRobert Bosch GmbH is a multinational engineering and technology company that develops automotive components, industrial technology, consumer goods, and energy solutions. The company operates across multiple sectors including mobility solutions, industrial technology, consumer goods, and building technologies.
10,001+
Employees
Gerlingen
Headquarters
Reviews
3.7
10 reviews
Work Life Balance
3.2
Compensation
3.8
Culture
4.1
Career
4.3
Management
2.9
72%
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Pros
Great people and team environment
Career development and learning opportunities
Good compensation and benefits
Cons
Poor work-life balance expectations
Management issues and favoritism
Lack of clear policies
Salary Ranges
711 data points
Senior/L5
Senior/L5 · Business Development Manager - Press
1 reports
$175,455
total / year
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$152,570
Stock
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Bonus
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$175,455
$175,455
Interview Experience
7 interviews
Difficulty
2.4
/ 5
Duration
14-28 weeks
Offer Rate
71%
Experience
Positive 14%
Neutral 86%
Negative 0%
Interview Process
1
Application Review
2
Recruiter Screen
3
Technical Interview Round 1
4
Technical Interview Round 2
5
HR Round/Salary Negotiation
6
Offer Extended
Common Questions
Technical Knowledge
Coding/Algorithm
Behavioral/STAR
Past Experience
Project-based Assessment
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