AI/ML Engineer – GenAI & Cloud Solutions

Bosch Group

New

Mid 🇬🇧 English

Python SQL HTML CSS JavaScript LangChain LangGraph AWS Bedrock Azure OpenAI Azure AI Search RAG embeddings vector retrieval prompt engineering evaluation metrics guardrails FastAPI Flask Plotly Dash Azure App Service Cloud Run Azure Bot Service Dialogflow Azure Data Factory BigQuery Databricks Azure Synapse Blob Storage Cloud Storage Document AI Power BI Tableau Looker QuickSight ThoughtSpot Docker CI/CD pipelines MLOps Azure GCP AWS

Job description

About the role

We are looking for an experienced AI/ML Engineer (4‑8 years) to design, develop, and deploy end‑to‑end GenAI and machine‑learning solutions on cloud platforms. You will work with cross‑functional teams to turn business challenges into scalable AI products.

Key responsibilities

Design and implement ML and GenAI solutions, including RAG pipelines, LLM integrations, prompt engineering, and guardrail frameworks.
Develop API‑based AI applications using FastAPI, Flask, or Plotly Dash.
Build complete ML pipelines: data ingestion, feature engineering, model training, validation, deployment, and monitoring.
Deploy workloads on Azure, GCP, or AWS services such as Azure App Service, Cloud Run, Azure Bot Service, and Dialogflow.
Implement MLOps workflows for CI/CD, model registry, experiment tracking, and automated retraining.
Create and optimise ETL/ELT pipelines with Azure Data Factory, BigQuery, Databricks, etc.
Produce dashboards and analytical insights using Power BI, Tableau, Looker, QuickSight, or ThoughtSpot.
Ensure solutions are scalable, secure, and cost‑optimized across cloud environments.

Required profile

4‑8 years of hands‑on experience in AI/ML, GenAI, data engineering, and cloud‑native deployments.
Proven ability to translate business requirements into AI‑driven outcomes.
Strong collaboration skills with cross‑functional teams.

Required skills

Python (advanced), SQL (strong), HTML/CSS/JavaScript (working knowledge).
LLM frameworks: LangChain, LangGraph, Google Vertex AI, AWS Bedrock, Azure OpenAI, Azure AI Search.
GenAI concepts: RAG, embeddings, vector retrieval, prompt design, evaluation metrics, guardrails.
Data platforms: BigQuery, Azure Synapse, Azure Data Factory, Databricks, Blob Storage, Cloud Storage, Document AI.
BI tools: Power BI, Tableau, Looker, QuickSight, ThoughtSpot.
DevOps/MLOps: Docker, CI/CD pipelines, model deployment & monitoring.
Cloud services: Azure, GCP, AWS (App Service, Cloud Run, Bot Service, Dialogflow, etc.).

Questions fréquentes

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Source : ats:smartrecruiters

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Published 12 hours ago

Expires 1 month from now

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