Responsibilities

Design, develop, and implement AI and machine learning models to address complex cybersecurity and business challenges.
Contribute to the continuous evolution of an automated cybersecurity platform.
Integrate cutting-edge AI models across the platform lifecycle to enhance automation, detection, and intelligence.
Collaborate closely with data scientists, software engineers, and stakeholders to embed AI solutions into production systems.
Perform data preprocessing and feature engineering to prepare datasets for modeling and analysis.
Conduct experiments to evaluate model performance and fine-tune algorithms and hyperparameters.
Stay up to date with the latest advancements in AI, machine learning, and cybersecurity.
Document AI methodologies, code, and project progress to support transparency and knowledge sharing.

Basic qualifications

5+ years of experience in artificial intelligence, machine learning, or related roles.
Strong proficiency in Python (or R) and experience with AI/ML libraries such as TensorFlow, PyTorch, or Scikit-learn.
Solid understanding of machine learning algorithms, NLP, and computer vision techniques.
Solid understanding of Docker, CI/CD pipelines, and scalable backend design.
Experience working with cloud-native environments and Kubernetes on AWS, Azure, or GCP.
Strong problem-solving skills and the ability to communicate complex concepts to both technical and non-technical stakeholders.
Hands-on experience with cloud-based AI solutions.
Knowledge of DevOps practices and version control systems (e.g., Git).
Familiarity with big data technologies such as Hadoop or Spark.
Publications or contributions to open-source AI projects.

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Remote Ai Ai Engineer Machine Learning