Machine Learning Engineer - Talent Groups - Irving, TX, US | Dice.com

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Machine Learning Engineer

Irving, TX, US • Posted 8 hours ago • Updated 8 hours ago

Contract W2

No Travel Required

On-site

$65+

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🛠️ Calibrating flux capacitors...

Job Details

Skills

AI
ML
Python
SQL
LangChain
Generative Artificial Intelligence (AI)
Machine Learning (ML)
Large Language Models (LLMs)
Machine Learning Operations (ML Ops)
NumPy
PyTorch
Pandas
TensorFlow
scikit-learn

Summary

Onsite, 4 days per week in Irving, TX 75038. Remote, one day per week.

Our Irving-based client is seeking a Full-Stack AI/ML Engineer to design, build, and deploy AI-driven solutions that transform data into production-ready intelligence. This role spans the full AI lifecycle from data acquisition and model development to LLM integration, deployment, and continuous optimization. The engineer will collaborate closely with product owners, program managers, and cross-functional Scrum teams to deliver scalable, high-impact AI capabilities aligned with business goals.

Key Responsibilities

Design and implement AI/ML solutions that automate, optimize, and enhance business workflows.
Acquire and preprocess structured and unstructured data from APIs, databases, OCR pipelines, and document sources.
Conduct exploratory data analysis (EDA) and build predictive and statistical models using Python and modern ML frameworks.
Develop and fine-tune Large Language Model (LLM) pipelines using tools such as OpenAI, Azure OpenAI, Hugging Face, and LangChain.
Implement retrieval-augmented generation (RAG) and document intelligence systems.
Develop and deploy production-grade APIs and microservices (FastAPI or similar) integrated with MLOps best practices.
Collaborate with data engineers on pipeline efficiency and software engineers on product integration.
Monitor, retrain, and optimize deployed models for performance and accuracy.
Research and prototype emerging AI techniques, including multimodal models and AI agents.
Document architectures, design decisions, and experiment outcomes for transparency and reproducibility.
Contribute as an active member of an Agile/Scrum team through sprint planning, backlog grooming, and daily stand-ups.
Participate in code reviews, maintain clean coding standards, and contribute to shared AI libraries and internal frameworks.

Qualifications

5+ years of hands-on experience in data science, ML engineering, or applied AI with production deployments.
Strong proficiency in Python (Pandas, NumPy, scikit-learn, LangChain, LangGraph, etc.) and SQL.
Experience with ML frameworks such as TensorFlow or PyTorch.
Skilled in data acquisition, ETL pipelines, and feature engineering across APIs, cloud storage, and databases.
Proficiency in FastAPI for model deployment as microservices.
Experience with MLOps tools and practices (Docker, Kubernetes, CI/CD).
Hands-on experience with cloud platforms (Azure, AWS, or Google Cloud Platform) and their AI/ML ecosystems.
Working knowledge of LLMs and Generative AI frameworks.
Strong understanding of EDA, model validation, and experiment tracking.
Familiarity with vector databases for semantic search and RAG workflows.
Comfortable in Agile/Scrum environments with strong communication and documentation skills.
Proven ability to take AI/ML models from prototype to production and drive continuous improvement.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.

Dice Id: 91099677
Position Id: 227712
Posted 8 hours ago

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