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Codvo AI · IT - Software Development

AI/ML Engineer

India, Bangalore · Job Posted June 03, 2026
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Job Description

We are seeking a highly skilled AI/ML Engineer to design, develop, and deploy scalable machine learning and deep learning solutions. The ideal candidate will have strong experience in computer vision, deep learning frameworks, and cloud-based ML deployment, along with solid software engineering and MLOps practices. You will work closely with cross-functional teams to build production-ready AI systems that deliver real business impact.

Job Responsibility

  • Design, develop, and optimize machine learning and deep learning models using PyTorch
  • Build and deploy computer vision solutions for real-world use cases
  • Develop end-to-end ML pipelines, including data ingestion, preprocessing, training, validation, and deployment
  • Implement and maintain MLOps workflows for model versioning, monitoring, CI/CD, and retraining
  • Deploy and scale ML models on AWS cloud infrastructure
  • Work with large-scale datasets using Databricks and distributed computing frameworks
  • Collaborate with data scientists, product managers, and software engineers to translate business requirements into AI solutions
  • Ensure high code quality by following software engineering best practices (modular design, testing, documentation)
  • Monitor model performance in production and continuously improve accuracy, efficiency, and reliability

Requirements

  • Strong proficiency in Python for machine learning and software development
  • Hands-on experience with PyTorch for deep learning model development
  • Solid understanding of deep learning architectures (CNNs, transfer learning, etc.)
  • Practical experience in computer vision applications
  • Experience working with Databricks and large-scale data processing
  • Strong knowledge of AWS services for ML deployment (EC2, S3, SageMaker, etc.)
  • Experience with MLOps tools and practices (model deployment, monitoring, CI/CD)
  • Good understanding of software engineering principles and production-grade system design

Nice to have

  • Experience with optimization and performance tuning of ML models
  • Knowledge of data security and compliance in cloud environments
  • Experience with monitoring tools for ML model performance and drift detection
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