Please mention work permit and Linkedin profile along with resume.
Job Title: AI Engineer
Location: Remote
No h1b and CPT
Position Overview
We are seeking a skilled AI Engineer to design, develop, and scale advanced artificial intelligence solutions across the enterprise. This role will focus on transforming existing prototypes into production-grade systems, improving model accuracy, enhancing reliability, and reducing hallucinations across GenAI and NLP workloads.
The ideal candidate has strong hands-on experience in GenAI, NLP, supervised learning, LangChain, and Python-based ML frameworks, along with the ability to integrate AI systems into enterprise environments.
Key Responsibilities
AI/ML Development
- Design and advance GenAI, NLP, and supervised learning models for contract extraction, classification, and interactive question-answering tools.
- Develop and maintain ML pipelines for supervised classification using curated and labeled datasets.
- Build and enhance conversational analytics tools for sales, customer service, and operational teams.
System Architecture & Integration
- Refactor current prototypes for enterprise scalability, accuracy, security, and improved user experience.
- Work closely with Data Engineers to integrate AI models with business systems, APIs, data platforms, and enterprise services.
- Develop robust workflows for model deployment, monitoring, and maintenance.
Quality Assurance & Monitoring
- Test and evaluate AI outputs for accuracy, hallucination reduction, and overall model reliability.
- Continuously monitor model performance and implement improvements to ensure high-quality production results.
- Establish quality assurance processes for model validation and tuning.
Required Qualifications
- 2+ years of hands-on experience with GenAI, LangChain, LLM frameworks, and prompt engineering.
- 3+ years of experience in machine learning or AI engineering roles.
- Strong proficiency in Python and AI/ML libraries: TensorFlow, PyTorch, Hugging Face Transformers, Scikit-learn, etc.
- Experience with NLP, document extraction, LLM-based agents, and conversational AI.
- Proven experience working with APIs, microservices, and enterprise data environments.
- Track record of building and deploying production-scale ML solutions.
Preferred Skills (Optional)
- Experience with vector databases (e.g., Pinecone, FAISS, ChromaDB).
- Familiarity with cloud-based AI services (Azure AI, AWS Sagemaker, GCP Vertex AI).
- Understanding of MLOps and CI/CD pipelines for machine learning.
- Experience with RAG (Retrieval-Augmented Generation) architectures.
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