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AI/ML Engineer with React -- Onsite -- Only W2 Profiles

Trebecon LLCManor, TX🇺🇸United StatesPosted 24 Aug 2026

Quick Overview

Seniority
Mid Senior
Work mode
On Site
Location
Manor, TX, United States
Posted
Yesterday
DockerFastAPIFlaskMicroservicesMongoDBMySQLNode.jsAWSMachine LearningNLPAgileAzureCSSGenerative AIGitGoogle CloudHTMLJavaScriptPostgreSQLPythonRESTReactTypeScript

Job Description

Role : AI/ML Engineer with React – Full Stack
Location: Austin, TX – Onsite

Key Responsibilities
  • Design, develop, and deploy Machine Learning and AI solutions for business use cases.
  • Build responsive and scalable React.js applications integrated with AI/ML services.
  • Develop backend services and RESTful APIs using Python, FastAPI, Flask, Node.js, or similar technologies.
  • Work with Generative AI, Large Language Models (LLMs), RAG, prompt engineering, embeddings, and vector databases.
  • Integrate AI/ML models into production applications using APIs and microservices.
  • Develop reusable React components, dashboards, forms, and interactive UI features.
  • Perform data preprocessing, feature engineering, model training, evaluation, and optimization.
  • Work with cloud platforms such as AWS, Azure, or Google Cloud Platform.
  • Collaborate with data scientists, software engineers, product teams, and business stakeholders.
  • Implement authentication, authorization, logging, monitoring, and secure API integrations.
  • Optimize application performance, scalability, and AI/ML model inference latency.
  • Participate in code reviews, testing, CI/CD, and production deployments.
Required Skills
  • 8+ years of relevant IT experience.
  • Strong hands-on experience with Python and Machine Learning.
  • Strong experience with React.js and full-stack application development.
  • Proficiency in JavaScript/TypeScript, HTML, and CSS.
  • Experience building and consuming REST APIs.
  • Strong understanding of Machine Learning algorithms, NLP, Generative AI, and AI/ML concepts.
  • Hands-on experience with LLMs, RAG, LangChain or LlamaIndex, embeddings, and vector databases.
  • Experience with databases such as PostgreSQL, MySQL, MongoDB, or similar technologies.
  • Experience with Git, Docker, CI/CD, and cloud deployments.
  • Strong understanding of SDLC and Agile methodologies.
 

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