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# Data Science/ML Engineer

- **Company:** Synechron Inc
- **Location:** Charlotte, NC, United States
- **Salary:** $110,000 - $120,000
- **Contract:** Permanent contract
- **Skills:** LangGraph Framework, Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Information Engineering, Monitoring of Systems, Machine Learning, Natural Language Processing, Software Deployment, Google Cloud, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Prompt Engineering, Generative AI, Fastapi, AI Platforms, Information Technology, Deployment Automation, Machine Learning Operations, Evaluation of Large Language Models, Restful APIs, GPT
- **Published:** November 8, 2026
- **Apply:** https://www.thejobnetwork.com/job/bea4c50b-47b8-4d90-89ee-40f12a731607/data-scienceml-engineer

## About the Role

* Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related field.
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 * Experience in Machine Learning, Data Science, or AI Engineering.
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 * Hands-on experience building and deploying enterprise-grade Generative AI applications.
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 * Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
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 * Strong understanding of MLOps, model monitoring, and production deployment practices.
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 * Familiarity with LLM evaluation, observability, and responsible AI principles.
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## Description

We are seeking a highly skilled Data Science / Machine Learning Engineer to design, develop, and deploy advanced AI/ML solutions leveraging Large Language Models (LLMs), Retrieval Augmented Generation (RAG), Natural Language Processing (NLP), and Machine Learning techniques. The ideal candidate will be responsible for building intelligent AI applications, developing prompt engineering frameworks, implementing retrieval pipelines, conducting model evaluations, and delivering scalable production-grade AI capabilities., n
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 * Develop LLM, RAG, NLP, and ML solutions. Build prompts, retrieval pipelines, evaluations, and production AI capabilities.
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 * Design, develop, and deploy AI/ML solutions using LLMs, NLP, and traditional Machine Learning techniques.
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 * Build and optimize RAG (Retrieval Augmented Generation) systems utilizing vector databases and embedding models.
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 * Develop effective prompt engineering strategies to improve model performance and business outcomes.
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 * Create evaluation frameworks to measure model accuracy, relevance, hallucination rates, and overall effectiveness.
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 * Implement guardrails, safety mechanisms, and hallucination detection techniques for enterprise AI applications.
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 * Develop and maintain AI orchestration workflows using LangChain and LangGraph.
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 * Fine-tune and optimize transformer-based models for domain-specific use cases.
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 * Build scalable APIs and AI services using FastAPI.
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 * Work closely with data engineering, product, and business teams to gather requirements and deploy production-ready solutions.
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 * Monitor, troubleshoot, and continuously improve AI/ML systems in production environments.
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 * Implement CI/CD pipelines and MLOps best practices for automated deployment and monitoring.
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