Devops engineer • des moines ia
Must Have Technical/Functional Skills.Looking for an experienced AI Engineer (6–8 years) to design, develop, and deploy cutting-edge AI/ML solutions.The ideal candidate will have strong experience ... Show more
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Location 8040 UNIVERSITY BLVD, Des Moines, IA, 50325, United States.Description Requirements Summary. Show more
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Disclaimer: This is not a federal position.This role is offered through a partnership agreement and does not constitute an NRCS hiring action.This position is a non-federal role funded through an e... Show more
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The average salary range is between $ 117,000 and $ 145,000 year , with the average salary hovering around $ 134,500 year .
The average salary range is between $ 109,997 and $ 165,000 year , with the average salary hovering around $ 129,990 year .
Must Have Technical/Functional Skills
Looking for an experienced AI Engineer (6–8 years) to design, develop, and deploy cutting-edge AI/ML solutions. The ideal candidate will have strong experience in machine learning, deep learning, data engineering, and building scalable AI systems for real-world applications.
Responsibilities:
• Build and optimize ML/Deep Learning models for NLP, CV, and predictive analytics.
• Develop end to end AI pipelines including training, deployment, and monitoring.
• Deploy models using Docker/Kubernetes and cloud platforms (Azure/AWS/GCP).
• Work with large datasets and build data pipelines using Python, SQL, and Spark/Databricks.
• Implement MLOps practices (CI/CD, model tracking, monitoring).
• Collaborate with cross functional teams to translate business needs into AI solutions.
Technical Skills
• Programming Languages: Python (strong expertise), SQL
• ML/DL Frameworks: TensorFlow, PyTorch, Scikit-learn
• NLP/LLM Tools: Transformers, LangChain, OpenAI APIs
• Cloud Platforms: Azure/AWS/GCP (at least one required)
• MLOps: MLflow, Kubernetes, Docker, Git
• Big Data Tools: Spark, Hive, Databricks (preferred)
Experience
• 4–6 years of experience in AI/ML engineering roles.
• End-to-end experience from data preparation to model deployment.
• Building scalable production grade AI solutions.
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