AI/ML Engineer: Generative AI & LLM Pipelines

Robotics Technologies LLC; Plano (TX); On-site; USD 120,000 - 180,000; Full time

Job summary

Robotics Technologies LLC seeks an experienced AI/ML Engineer with strong Python skills to develop and deploy scalable AI/ML models and enterprise-ready RAG applications. The role focuses on end-to-end model development, evaluation, and production readiness, including LLM-based solutions.

You will design and build RAG pipelines, leverage embeddings and vector databases, and integrate solutions via APIs and microservices while collaborating with data engineering, cloud, DevOps, QA, architecture,

Qualifications

• Experience building and deploying AI/ML models in production.
• Strong Python programming and end-to-end ML development.
• Experience with ML/DL frameworks (TensorFlow and/or PyTorch).

Responsibilities

• Analyze business requirements and design scalable AI/ML solutions.
• Develop, train, evaluate, and optimize ML, deep learning, NLP, and Generative AI models.
• Build LLM applications and RAG pipelines using embeddings, vector databases, prompt engineering, and orchestration frameworks.
• Integrate AI/ML solutions into enterprise platforms through APIs and microservices.
• Collaborate with data engineering, cloud, DevOps, QA, architecture, and business teams.
• Implement production practices including CI/CD, testing, containerization, model versioning, monitoring, and performance optimization.
• Support model troubleshooting, drift detection, observability, and continuous improvement.

Skills

Python development

ML / DL

TensorFlow / PyTorch

Generative AI / NLP

Tools

GitHub Actions

Job description

Robotics Technologies LLC seeks an experienced AI/ML Engineer with strong Python skills to develop and deploy scalable AI/ML models and enterprise-ready RAG applications. The role focuses on end-to-end model development, evaluation, and production readiness, including LLM-based solutions.

You will design and build RAG pipelines, leverage embeddings and vector databases, and integrate solutions via APIs and microservices while collaborating with data engineering, cloud, DevOps, QA, architecture,