AI / ML Engineer

🕒 April 24

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Codvo.ai

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2019

🔒 Cybersecurity

☁️ SaaS

AI • Cybersecurity • SaaS

Codvo. ai is a technology company that specializes in delivering strategic enterprise solutions through advanced AI-driven innovation. They focus on transforming enterprise data into measurable value by helping businesses accelerate growth with custom AI implementations tailored to meet the specific challenges of various industries. Their extensive service offerings include AI/ML automation, application development, data analytics, cybersecurity, and digital transformation, ensuring that organizations can thrive in a rapidly evolving digital landscape.

📋 Description

• 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 • Monitor model performance in production and continuously improve accuracy, efficiency, and reliability

🎯 Requirements

• 5+ years of experience in AI/ML engineering • Strong proficiency in Python • Hands-on experience with PyTorch • 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 • Good understanding of software engineering principles