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# Lead AI Data Engineer

- **Company:** Unisoft Technology Inc
- **Location:** United States
- **Experience:** Expert
- **Contract:** Permanent contract
- **Skills:** Airflow, Amazon Web Services, Information Engineering, Python (Programming Language), Cloud Services, Tensorflow, Azure Machine Learning, Pytorch, Large Language Models, Prompt Engineering, Containerization, Scikit Learn, Kubernetes, Information Technology, HuggingFace, Machine Learning Operations, Docker
- **Published:** August 12, 2026
- **Apply:** https://www.dice.com/job-detail/8131fdbc-001b-40e6-968c-55068f5203ab

## About the Role

Bachelor''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''''s degree in Computer Science, Data Science, Engineering, or a related field

15+ years of experience in software or data engineering, with at least 4 years focused on ML systems or MLOps in a production environment.

Demonstrated experience building or operating a shared/enterprise ML platform serving multiple teams or business units.

Strong proficiency in Python and familiarity with ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn, Hugging Face).

Hands-on experience with MLOps tooling: Kubeflow, MLflow, Airflow, or equivalent.

Experience with cloud-native data and ML services on AWS.

Working knowledge of LLMs, prompt engineering, and RAG architecture patterns.

Experience with containerization and orchestration (Docker, Kubernetes).

Strong understanding of data engineering concepts: pipelines, feature stores, data quality, and lineage.



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- [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology)
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- [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered)
- [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment)
- [DevOps for AI: running LLMs in production with Kubernetes and KubeFlow](https://www.wearedevelopers.com/videos/1222-devops-for-ai-running-llms-in-production-with-kubernetes-and-kubeflow)

## Related Articles

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