Demo

AI Engineer

EXOS IT
Indianapolis, IN Full Time
POSTED ON 3/12/2025
AVAILABLE BEFORE 4/10/2025

What You Will Do:


Machine Learning & AI Model Development

  • Design and train machine learning models for classification, regression, clustering, and recommendation systems.
  • Develop deep learning models using frameworks like TensorFlow or PyTorch for applications such as image recognition, NLP, and speech processing.
  • Optimize AI models for performance, accuracy, and efficiency.

Natural Language Processing (NLP)

  • Implement NLP solutions for sentiment analysis, chatbots, document processing, and text summarization.
  • Work with pre-trained models like GPT, BERT, and LLaMA, fine-tuning them for specific use cases. o Develop AI-driven automation for extracting insights from unstructured data sources.

AI Model Deployment & Infrastructure

  • Deploy AI models in production using cloud services (AWS, Azure, GCP) or on-premises solutions.
  • Develop APIs and microservices to integrate AI models with business applications.
  • Monitor and maintain deployed models, retraining them as needed to ensure continued performance.

Data Engineering & Feature Engineering

  • Work with large datasets, applying data cleaning, preprocessing, and transformation techniques. o Engineer relevant features for training robust and high-performing AI models.
  • Optimize data pipelines for real-time AI processing where applicable.

AI Research & Innovation

  • Stay up to date with the latest AI advancements and research papers.
  • Experiment with generative AI, reinforcement learning, and emerging AI technologies.
  • Explore ways to leverage AI for solving complex business challenges.


What You Have Done:


  • Excellent organizational, written, and verbal communication skills.
  • Minimum 2 years of experience in AI development, machine learning, or a related field.
  • Strong programming skills in Python (preferred), with experience using TensorFlow, PyTorch, or Scikit-learn.
  • Experience working with cloud-based AI services such as AWS SageMaker, Azure AI, or Google Vertex AI.
  • Understanding of machine learning concepts, feature engineering, and model optimization techniques.
  • Familiarity with MLOps practices, including model deployment and monitoring.
  • Ability to work with structured and unstructured data for AI model training and evaluation.
  • Experience working with large language models (LLMs) and fine-tuning AI models.
  • Understanding of ethical AI, bias mitigation, and model explainability.
  • Experience integrating AI solutions with APIs and business applications.
  • AI-related certifications such as AWS Certified Machine Learning – Specialty, Microsoft AI Engineer Associate, or equivalent are a plus.

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