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Roles & Responsibilities:
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Implementation & validation of AI-powered solutions with modular, reusable components using Python, REST APIs & in-house developed AI framework/s.
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Contribute to the development of AI pipelines, from data ingestion to model deployment and monitoring.
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Collaborate across domains to integrate AI/LLM capabilities to realize use cases such as AI-powered ASPICE assessments, Artefacts evaluation, etc.
Optimize agent behavior for safety, efficiency, and explainability.
Technical Skills:
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Strong programming background in Python with experience in AI/ML frameworks (e.g., Lang Chain, Hugging Face, OpenAI APIs).
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Knowhow of RAG concept.
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Understanding of LLMs, Embeddings, and multi-model reasoning.
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API orchestration, and GenAI prompt engineering.
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Familiarity with tools like Git,GITHUB ,versioning concepts.
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Strong analytical and problem-solving skills with a user-centric design mindset.
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Familiarity of A2A,MCP protocols.+
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Workflow Management: Experience with workflow automation tools like Power Automate, n8n,
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Hands-on experience with GenAI foundation models and vector databases, leveraging foundational AI models for advanced capabilities.
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Familiarity with automotive standards such as ASPICE PAM model .(Good to have)
Educational qualification:
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Any Bachelor’s or Master’s degree
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3–4 years of hands-on experience in AI model development, deployment, and optimization.
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Strong command of Python and libraries
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Deep understanding of machine learning algorithms, model training workflows, and deep learning architectures (CNN, RNN, Transformers).
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Experience with data wrangling, preprocessing, and feature engineering for model readiness.
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Skilled in developing and integrating models via APIs(Flask, FastAPI) and containerization using Docker.
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Proficiency in model evaluation metrics, hyperparameter tuning, and performance analysis.
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Experience with Git and collaborative code development workflows.
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Strong analytical mindset and ability to troubleshoot complex model behaviors.
Preferred Qualifications:
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Experience working with Large Language Models (LLMs),Generative AI, or prompt engineering
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Familiarity with cloud AI platforms
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Knowledge of MLOps practices — CI/CD for ML, model monitoring, and retraining pipelines.
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Exposure to computer vision or NLP-based AI systems.
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3–4 years of hands-on experience in AI model development, deployment, and optimization.
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
Base
$152,570
Stock
-
Bonus
-
$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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