AI/ML Engineer
Listed on 2026-01-10
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IT/Tech
AI Engineer, Machine Learning/ ML Engineer, Data Scientist
AI / ML Engineer
Location:
Dallas, TX
We are seeking an experienced AI/ML Engineer with strong expertise in Agentic AI systems and orchestration frameworks such as Lang Chain, CrewAI, Agno, combined with hands‑on experience in Machine Learning using Python for both textual and tabular data. The ideal candidate will have a solid background in cloud platforms, CI/CD pipelines, and secure agentic system design, along with practical knowledge of MLOps/LLMOps best practices.
Experience with Telecom billing systems is a plus.
We are seeking an experienced AI/ML Engineer with strong expertise in Agentic AI systems and orchestration frameworks such as Lang Chain, CrewAI, Agno, combined with hands‑on experience in Machine Learning using Python for both textual and tabular data. The ideal candidate will have a solid background in cloud platforms, CI/CD pipelines, and secure agentic system design, along with practical knowledge of MLOps/LLMOps best practices.
Experience with Telecom billing systems is a plus.
- Agentic AI Development
- Design and implement Agentic AI architectures using orchestration tools like Lang Chain, CrewAI, Agno.
- Build secure, scalable multi‑agent systems for enterprise workflows.
- Integrate LLMs and external APIs for dynamic reasoning and task execution.
- Exposure to vector databases (Pinecone, Weaviate, Azure AI Search, Neo4j) and retrieval‑augmented generation (RAG).
- Machine Learning & Data Handling
- Develop ML models for text analytics (NLP, embeddings, transformers) and tabular data (classification, regression, clustering).
- Optimize algorithms for performance and accuracy using Python and popular ML libraries (Tensor Flow, PyTorch, Scikit‑learn).
- Cloud & Deployment
- Deploy AI/ML solutions on AWS, Azure, or GCP with best practices for scalability and security.
- Implement CI/CD pipelines for automated testing, deployment, and monitoring of AI systems.
- MLOps / LLMOps
- Establish model lifecycle management, including versioning, monitoring, and retraining.
- Implement LLMOps workflows for prompt management, evaluation, and fine‑tuning of large language models.
- Security & Compliance
- Design secure agentic systems with proper authentication, authorization, and data privacy controls.
- Ensure compliance with enterprise security standards
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