Senior AI & Generative AI Specialist
Bosch
Company Description
The Bosch Group is a leading global supplier of technology and services, in the areas of Automotive Technology, Industrial Technology, Consumer Goods, Energy and Building Technology.
In India, the Group operates through nine companies with a combined strength of over 30,000 associates which includes around 14,000 research and development associates.
Bosch Automotive Electronics India Pvt. Ltd. (RBAI) is a 100% subsidiary of Robert Bosch GmbH. RBAI was established at the right time to cater to the demands of future Indian market. Established in 2009, started out with manufacturing Electronic Control Units. On an average adding one new product every year, Antenna and Immobilizer in 2011, wide range of BCM's since 2012, Electronic power steering control units from 2013, and Voltage regulator in 2014. Over the last 7 years of its existence, the company has grown over 44% CAGR, which is remarkable considering it was established during the peak of recession.
The product portfolio of Bosch Automotive Electronics Pvt. Ltd. is into both Automotive and Non-Automotive Business catering to local as well as global demands. The products from RBAI fulfils 94% of the local demand. Apart from this, 72% of our sales are towards exports covering most of the global market.
We invite promising and dynamic professionals for a long-term and
rewarding career with Bosch.
Job Description
Role Summary
We are seeking a Senior AI & Generative AI Specialist to architect, build, and scale production-grade AI and GenAI solutions. The role demands deep hands-on expertise, strong system architecture skills, and the ability to lead cross-functional teams delivering result oriented & compliant AI systems.
This role will own end-to-end AI lifecycle — from problem framing and model design to deployment, monitoring, governance, and business impact — with a strong emphasis on Machine learning, GenAI, LLM fine-tuning, RAG systems, and Responsible AI.
Key Responsibilities
AI & GenAI Architecture
- Design and architect enterprise-scale AI and Generative AI systems, including LLM-based applications, RAG pipelines, fine-tuned models, and multimodal AI systems.
- Lead development of AI platforms and frameworks enabling reusable, scalable AI services (AI-as-a-Service).
- Define model selection strategies , fine-tuning approaches, and inference optimization.
Machine Learning & Deep Learning
- Develop and deploy advanced ML/DL models across:
- Computer Vision (segmentation, detection, classification)
- NLP (BERT, GPT, Transformers)
- Generative AI (Diffusion models, GANs, multimodal systems)
- Time-series forecasting, predictive analytics, anomaly detection
- Drive model optimization, hyperparameter tuning, and performance benchmarking.
- Ensure model explainability, fairness, bias detection, and mitigation.
GenAI & LLM Systems
- Build GenAI applications & Agents including:
- Intelligent document processing
- Automated report generation
- Smart ticketing and customer escalation systems
- Knowledge assistants using RAG + vector databases
- Implement prompt engineering, evaluation frameworks, and guardrails.
- Optimize inference cost, latency, and scalability in cloud environments.
MLOps & Production Deployment
- Establish MLOps best practices:
- CI/CD for ML
- Model versioning and monitoring
- Automated retraining pipelines
- Deploy AI services using Docker, Kubernetes, MLflow, FastAPI, Flask.
- Ensure high availability, low latency, and cloud cost optimization.
Cloud & Big Data
- Architect AI workloads on Azure, Databricks, Spark.
- Build scalable data pipelines for large-scale training and inference.
- Leverage distributed computing for large datasets and real-time inference.
Leadership & Stakeholder Engagement
- Consult and mentor AI engineering and data science teams.
- Collaborate with the AI working group & international stakeholder community.
- Translate business and domain problems into AI solutions with measurable impact.
- Drive innovation initiatives, patents, and hackathon-level experimentation.
Qualifications
- Master’s degree in Data Science, AI, or related field
- Experience in AI , Agentic AI , Advance data analytics usecases in a manufacturing environment
- Strong understanding of AI governance and compliance
- >8 years of experience in buildup and delivery of AI/ML usecases with proven business benefits
- Leadership of AI/ML teams would be an added advantage
Required Technical Skills
Programming & Frameworks
- Python (expert), PyTorch, Keras, PySpark, SQL
- REST API development: FastAPI, Flask
- Version control & CI/CD: Git, GitHub Actions
AI / ML
- Supervised & Unsupervised Learning
- Deep Learning: CNNs, RNNs, Transformers
- Generative AI: LLMs, Diffusion models, GANs
- Reinforcement Learning (applied understanding)
NLP & Computer Vision
- BERT, GPT, Text Summarization, NER
- Speech-to-Text / Text-to-Speech
- Image segmentation, object detection, multimodal AI
Cloud & MLOps
- AWS, Azure, Databricks, Spark
- Docker, Kubernetes, MLflow
- Scalable inference engines
Additional Information
Impact & Success Metrics
- Deliver AI systems with measurable business outcomes (efficiency, accuracy, cost reduction).
- Reduce manual workloads through automation and GenAI adoption.
- Improve decision-making accuracy using explainable and responsible AI.
- Scale AI platforms adopted across multiple plants & divisions