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AI Engineer

Job in Passaic, Passaic County, New Jersey, 07055, USA
Listing for: Futran Tech Solutions Pvt. Ltd.
Full Time position
Listed on 2026-07-01
Job specializations:
  • IT/Tech
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer, AI Business & Operations, AI Evaluation
Job Description & How to Apply Below

AI Engineer

The Applied AI role focuses on developing, deploying, and optimizing artificial intelligence systems for real-world applications. The position bridges research and engineering by transforming AI models into scalable solutions that support large-scale AI training, evaluation, and automation workflows.

Key Responsibilities
  • Build, test, and deploy machine learning and AI models for practical business and product applications.
  • Implement algorithms and frameworks to improve model performance and reliability.
AI System Implementation
  • Integrate AI models into production systems and operational workflows.
  • Design pipelines for data processing, model training, and evaluation.
Research to Production
  • Translate AI research concepts into practical tools and scalable products.
  • Experiment with new machine learning techniques to enhance system capabilities.
Data and Model Optimization
  • Work with large datasets to train and fine-tune models.
  • Monitor model outputs and continuously improve accuracy and efficiency.
Cross-Functional Collaboration
  • Partner with engineers, product teams, and operations teams to build AI-driven solutions.
  • Support projects that help AI companies scale model training and evaluation.
Required

Skills & Qualifications
  • Strong background in Artificial Intelligence, Machine Learning, or Computer Science.
  • Experience with Python, ML frameworks, and large-scale data systems.
  • Knowledge of deep learning, model training, and evaluation methods.
  • Ability to translate research ideas into practical engineering solutions.
  • Strong analytical and problem-solving skills.
Impact of the Role
  • Enables the deployment of advanced AI systems in production environments.
  • Supports large-scale AI training and evaluation infrastructure.
  • Improves model performance and scalability for next-generation AI applications.
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