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Full Stack AI Developer at NTT DATA
Irving, Texas, United States -
Full Time

Start Date

Immediate

Expiry Date

14 Jan, 26

Salary

0.0

Posted On

16 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Python, HTML, CSS, JavaScript, Node.js, Django, TensorFlow, PyTorch, Scikit-learn, Angular, MongoDB, Microservices, AI, Machine Learning, APIs, Cloud Services

Industry

IT Services and IT Consulting

Description
Design and develop user-facing front-end elements, build and maintain secure, scalable backend services and APIs using modern frameworks. Integrate AI/ML models and services into applications, including designing, training, and deploying models for traditional and generative AI. Handle data pipelines, databases, and data warehousing to support AI model development and application functionality. Implement and manage machine learning operations to facilitate model training, deployment, monitoring, and version control in production environments. Work with cross-functional teams, including data scientists and product managers, to define and implement new features and AI-driven solutions. Debug issues, optimize application performance, and ensure scalability and security of both web applications and AI models. Overall 5+ years of experience 3+ Years of experience in languages like Python, along with front-end languages (HTML, CSS, JavaScript) and back-end technologies (Node.js, Django, etc.). 2+ Years of Experience with AI and machine learning frameworks such as TensorFlow, PyTorch, and Scikit-learn. Expertise in designing and developing scalable web applications and APIs. Familiarity with cloud services (e.g., AWS, Azure, GCP) for deploying and scaling AI and web applications. Experience with database systems (SQL, NoSQL) for data management and processing. Experience with Angular, MongoDB, Microservices, etc.
Responsibilities
Design and develop user-facing front-end elements and maintain secure, scalable backend services and APIs. Integrate AI/ML models into applications and manage machine learning operations for model training and deployment.