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.
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
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
