AI/ML Engineer with React - Full Stack

Trebecon LLC

Austin, TX, United States

1 day ago

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Role details

Contract type

Permanent contract

Employment type

Full-time (> 32 hours)

Experience level

Expert

Experience required

8 years minimum

Working hours

Regular working hours

Job source

www.dice.com

Tech stack

HTML JavaScript (Programming Language) Application Programming Interfaces (APIs) Artificial Intelligence Amazon Web Services Microsoft Azure Cascading Style Sheets (CSS) Databases Continuous Integration Data Cleansing Python (Programming Language) PostgreSQL

+22 more

Machine Learning MongoDB MySQL Natural Language Processing Node.Js Cloud Services TypeScript Data Logging Google Cloud Feature Engineering ReactJS Flask (Web Framework) Large Language Models Prompt Engineering Generative AI Backend Git Fastapi Information Technology Restful APIs Docker Microservices

Job description

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.

Requirements

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.