AI & Machine Learning Engineer / AI Solutions Architect
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Role details
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Job description
We are seeking a highly experienced Senior AI & Machine Learning Engineer / AI Solutions Architect with 10-15+ years of IT experience to design, build, and deploy enterprise-scale AI and Machine Learning solutions. The ideal candidate will have strong expertise in Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Agentic AI, MLOps, Deep Learning, NLP, Computer Vision, and cloud-based AI platforms., * Design and develop enterprise AI/ML applications and intelligent automation solutions.
- Build, fine-tune, and optimize Large Language Models (LLMs) and foundation models.
- Develop Retrieval-Augmented Generation (RAG) and AI Agent solutions.
- Design scalable AI architectures for enterprise applications.
- Build and deploy end-to-end ML pipelines from data ingestion to production.
- Develop AI-powered chatbots, copilots, recommendation engines, and predictive analytics solutions.
- Implement prompt engineering and model optimization techniques.
- Deploy AI solutions using MLOps best practices.
- Monitor, evaluate, and improve AI model performance in production.
- Collaborate with Data Engineers, Data Scientists, Software Engineers, and business stakeholders.
- Implement Responsible AI, governance, security, and compliance standards.
- Mentor engineering teams and provide technical leadership., * MLflow
- Kubeflow
- Azure Machine Learning
- AWS SageMaker
- Google Vertex AI
- Docker
- Kubernetes
- CI/CD for ML Pipelines
Vector Databases
- Pinecone
- ChromaDB
- FAISS
- Weaviate
- Milvus
Data Engineering
- Apache Spark
- Databricks
- Snowflake
- Apache Airflow
- Kafka
- Delta Lake
Cloud Platforms
- AWS
- Microsoft Azure
- Google Cloud Platform (Google Cloud Platform)
Databases
- PostgreSQL
- MongoDB
- MySQL
- Redis
DevOps & Tools
- Git
- GitHub
- Azure DevOps
- Jenkins
- Terraform
Requirements
- Python (Expert)
- SQL
- Java
- Scala
Artificial Intelligence & Machine Learning
- Machine Learning
- Deep Learning
- Generative AI
- Large Language Models (LLMs)
- Natural Language Processing (NLP)
- Computer Vision
- Reinforcement Learning
- Transfer Learning
- Fine-Tuning
- Prompt Engineering
- Retrieval-Augmented Generation (RAG)
- AI Agents / Agentic AI
- Multi-Agent Systems
AI Frameworks & Libraries
- PyTorch
- TensorFlow
- Keras
- Scikit-learn
- Hugging Face Transformers
- LangChain
- LlamaIndex
- DSPy
- OpenCV
LLM Platforms
- OpenAI
- Azure OpenAI
- Anthropic Claude
- Google Gemini
- Meta Llama
- Mistral AI
- Cohere, * Bachelor’’'’s or Master’’'’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
- 10-15+ years of IT experience, including 5+ years in AI/ML or Generative AI.
- Strong expertise in enterprise AI architecture and ML model deployment.
- Experience building production-grade AI and LLM applications.
- Strong knowledge of cloud-native AI services and MLOps.
- Excellent analytical, communication, and leadership skills. __________________
Preferred Experience
- Enterprise AI Copilots and conversational AI.
- RAG-based knowledge management systems.
- AI Agents and workflow automation.
- Fine-tuning open-source LLMs (Llama, Mistral, Falcon).
- Healthcare, Banking, Insurance, Retail, Manufacturing, or Telecom domains.
- AI governance, security, and Responsible AI frameworks., * Microsoft Certified: Azure AI Engineer Associate (AI-102)
- AWS Certified Machine Learning - Specialty
- Google Professional Machine Learning Engineer
- Databricks Certified Machine Learning Professional
- NVIDIA Deep Learning Institute Certifications
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