Data Science Engineer

Irving, TX - USA

Monthly Salary: Not Disclosed

Posted on: 15 hours ago

Vacancies: 1 Vacancy

Job Summary

Job Description

Must Have Technical/Functional Skills

Advanced Python development for ML/AI workloads

End to end ML lifecycle: model training evaluation fine tuning and labeling/tagging workflows

Generative AI systems design including LLM-based application development

Prompt engineering optimization for large language models

Document AI pipelines: OCR/extraction parsing normalization and text chunking for structured & unstructured data

Embedding generation pipelines for semantic search and retrieval

Vector similarity search implementation using vector databases

ML model integration with Vector DBs and MongoDB

Production grade ML engineering: scalable maintainable and deployment ready code

Python Large Language Models (LLMs) (via LLM based applications) Vector Databases MongoDB

Roles & Responsibilities

We are seeking a highly skilled Data Science Engineer to design and develop scalable ML and Generative AI solutions. The ideal candidate will have deep expertise in Python hands-on experience in model training document processing pipelines and strong knowledge of vector databases and modern ML/GenAI frameworks.

Strong fit if the candidate:

Has expert level Python skills

Has hands on experience building ML/GenAI systems not just theoretical knowledge

Has worked on end to end ML pipelines (data model deployment)

Has experience with document AI embeddings and vector search

Thinks like an engineer (scalable maintainable production ready code)

Likely not a fit if the candidate is:

Primarily a BI / reporting analyst

Focused only on statistical modeling or academic research

Lacking experience with deployment pipelines or GenAI systems

Key Responsibilities

Develop and deploy machine learning and GenAI solutions using Python

Design and optimize prompt engineering strategies for LLM-based applications

Build document extraction parsing and chunking pipelines for structured and unstructured data

Train evaluate and fine-tune ML models; manage tagging and labeling workflows

Implement embedding generation and vector search solutions

Integrate ML models with Vector DBs and MongoDB

Ensure code quality scalability and production readiness

Job Description Must Have Technical/Functional Skills Advanced Python development for ML/AI workloads End to end ML lifecycle: model training evaluation fine tuning and labeling/tagging workflows Generative AI systems design including LLM-based application developmen...