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 :
- Masters 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
Remote Work :
No
Employment Type :
Full-time
Role SummaryWe 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 ...
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 :
- Masters 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
Remote Work :
No
Employment Type :
Full-time
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