Senior AI/ML Engineer

Cynet Systems • Irving, TX

1d

About The Position

The organization is seeking a Senior AI/ML Engineer to design, develop, deploy, and scale AI solutions for enterprise use cases. The role requires hands-on expertise across machine learning, deep learning, MLOps, generative AI, and agentic AI. The engineer will collaborate with product, engineering, data, and business teams to translate business problems into AI solutions, and will mentor junior engineers and contribute to AI architecture and technology strategy.

The position involves building end-to-end ML and deep learning solutions, productionizing models, developing MLOps pipelines, building LLM-based applications and agentic workflows, integrating with enterprise systems, and deploying scalable solutions on cloud platforms. It also includes implementing monitoring, evaluation, observability, security, and responsible AI practices.

Requirements

• 5+ years of experience in AI/ML, Data Science, Machine Learning Engineering, or a related field.
• Hands-on expertise across machine learning, deep learning, MLOps, generative AI, and agentic AI.
• Programming experience with Python and SQL.
• Machine learning experience with Scikit-learn and XGBoost or LightGBM.
• Deep learning experience with PyTorch or TensorFlow.
• Generative AI experience with LLMs, prompt engineering, embeddings, and RAG.
• Agentic AI experience with LangGraph, LangChain, or equivalent frameworks.
• Vector search experience with OpenSearch, FAISS, Pinecone, or equivalent.
• MLOps experience with MLflow, Docker, CI/CD, model deployment, and monitoring.
• Experience with AWS, Azure, or GCP.
• API and engineering experience with REST APIs, FastAPI, Git, and containerization.

Responsibilities

• Design and develop end-to-end machine learning and deep learning solutions.
• Build and productionize machine learning models using appropriate algorithms and frameworks.
• Develop and manage MLOps pipelines for model training, deployment, monitoring, and lifecycle management.
• Build generative AI applications using LLMs, prompt engineering, embeddings, RAG, and vector databases.
• Design and implement agentic AI solutions, including AI agents, tool calling, multi-agent workflows, and orchestration.
• Integrate AI solutions with enterprise APIs, databases, applications, and knowledge sources.
• Deploy scalable AI solutions on AWS, Azure, or GCP.
• Implement AI application monitoring, evaluation, observability, security, and responsible AI practices.
• Collaborate with product, engineering, data, and business teams to translate business problems into AI solutions.
• Mentor junior engineers and contribute to AI architecture and technology strategy.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed