Overview
On Site
Depends on Experience
Contract - Independent
Contract - W2
Contract - 1 Year(s)
Skills
Artificial Intelligence
Amazon Web Services
AngularJS
Clustering
Collaboration
Continuous Delivery
Apache Cassandra
Apache Maven
Cascading Style Sheets
Cloud Computing
Jenkins
Keras
Kubernetes
Machine Learning (ML)
Management
Microservices
Microsoft Azure
MongoDB
MySQL
Natural Language Processing
NoSQL
PostgreSQL
Python
RESTful
React.js
Real-time
Regression Analysis
SQL
Scalability
TensorFlow
TypeScript
Vue.js
Web Applications
scikit-learn
Gradle
HTML5
Hibernate
Docker
Frontend Development
Git
Good Clinical Practice
Google Cloud Platform
JPA
Java
Continuous Integration
Css3
Data Processing
Database
Deeplearning4j
DevOps
JavaScript
Spring Framework
Job Details
Job Title: Java full stack with react and AI/ML exp
Client:
Implementation:
Duration: 6-12+ Months
Experience level: 12+ Experience
Location: Charlotte, NC, USA (Onsite)
Key Responsibilities
Full Stack Development:
- Develop and maintain web applications using Java (Spring Boot) for backend /React for frontend.
- Build RESTful APIs, microservices, and secure application layers.
- Ensure performance, security, and scalability of applications.
AI/ML Integration:
- Collaborate with data scientists to integrate ML models into production-grade systems.
- Use APIs or pipelines to deploy ML models in Java-based environments.
- Handle data processing, transformation, and real-time inference tasks.
DevOps & Deployment:
- Containerize applications using Docker and manage deployments via Kubernetes or cloud platforms (AWS, Google Cloud Platform, or Azure).
- Implement CI/CD pipelines and use monitoring tools for performance and reliability.
Required Skills:
Core Development:
- Proficient in Java, Spring Boot, REST APIs, Hibernate/JPA.
- Strong front-end development with Angular, React, or Vue.js.
- Hands-on with HTML5, CSS3, JavaScript, TypeScript.
AI/ML Exposure:
- Basic to intermediate understanding of ML concepts: classification, regression, clustering, NLP, etc.
- Ability to work with Python ML libraries (e.g., scikit-learn, TensorFlow, Keras) or Java-based ML tools like Deeplearning4j.
- Understanding of model APIs, feature engineering, and data pipelines.
Database & Tools:
- SQL (PostgreSQL, MySQL) and NoSQL (MongoDB, Cassandra).
- Git, Maven/Gradle, Jenkins, Docker, Kubernetes.
Thanks & Regards,
Sandeep Siliveru,
Lead Recruiter
Radient.AI
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