Data Science / ML Engineer

URGENT HIRING DATA SCIENCE / ML ENGINEER

Client: Synechron
Job Title: Data Science / ML Engineer
Location: Charlotte, NC
Work Model: Work from Office Onsite
Employment Type: W2 Only
Experience: Overall 10+ Years Required
Work Authorization: W2 Candidates Only

The Role

Responsibilities:

Develop LLM, RAG, NLP, and ML solutions. Build prompts, retrieval pipelines, evaluations, and production AI capabilities.

Design, develop, and deploy AI/ML solutions using LLMs, NLP, and traditional Machine Learning techniques.

Build and optimize RAG (Retrieval Augmented Generation) systems utilizing vector databases and embedding models.

Develop effective prompt engineering strategies to improve model performance and business outcomes.

Create evaluation frameworks to measure model accuracy, relevance, hallucination rates, and overall effectiveness.

Implement guardrails, safety mechanisms, and hallucination detection techniques for enterprise AI applications.

Develop and maintain AI orchestration workflows using LangChain and LangGraph.

Fine-tune and optimize transformer-based models for domain-specific use cases.

Build scalable APIs and AI services using FastAPI.

Work closely with data engineering, product, and business teams to gather requirements and deploy production-ready solutions.

Monitor, troubleshoot, and continuously improve AI/ML systems in production environments.

Implement CI/CD pipelines and MLOps best practices for automated deployment and monitoring.

Requirements

Programming & Data Analysis

Python

SQL

Pandas

Jupyter Notebook

Machine Learning & Data Science

Supervised and Unsupervised Machine Learning

Natural Language Processing (NLP)

Statistical Analysis

Model Evaluation Metrics:

Precision

Recall

F1 Score

ROC-AUC

Generative AI & LLM Technologies

Large Language Models (LLMs)

Transformers & Self-Attention Architectures

Prompt Engineering

Embeddings

Retrieval Augmented Generation (RAG)

Hallucination Detection and AI Guardrails

AI Frameworks & Evaluation Tools

LangChain

LangGraph

LangSmith

Galileo

Databases

MongoDB

Vector Databases (Pinecone, Weaviate, Chroma, Milvus, FAISS)

Application Development & DevOps

FastAPI

Git

Jenkins

CI/CD Pipelines

OpenShift

Linux

Preferred Qualifications

Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related field.

Experience in Machine Learning, Data Science, or AI Engineering.

Hands-on experience building and deploying enterprise-grade Generative AI applications.

Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.

Strong understanding of MLOps, model monitoring, and production deployment practices.

Familiarity with LLM evaluation, observability, and responsible AI principles.

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