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Machine Learning Engineer

About Us

ÆONIS SYSTEMS is looking for a Machine Learning Engineer to develop and deploy AI-driven solutions for healthcare and education. This role focuses on building scalable, high-performance machine learning models that integrate into real-world applications such as patient monitoring, medical analytics, and personalized learning systems. The ideal candidate has strong hands-on experience in model development, optimization, and deployment.

Important Note: Until funding is secured, we ask for a commitment of 10-15 hours per month to ensure steady progress while respecting your time and contributions. This role is open to global applicants and can be remote.

Key Responsibilities

  • Model Development: Train and optimize machine learning models for AI-powered healthcare and education systems.

  • Data Engineering: Preprocess, clean, and structure large-scale datasets for AI applications.

  • Algorithm Optimization: Improve the efficiency, scalability, and accuracy of ML models.

  • Collaboration: Work alongside AI researchers, software developers, and healthcare professionals to refine AI solutions.

  • Model Deployment: Implement models into real-world applications using cloud platforms and scalable infrastructures.

  • Ethical AI Practices: Ensure models meet ethical AI standards, focusing on bias mitigation and explainability.

Qualifications

  • Experience: Minimum 3+ years in machine learning model development and deployment.

  • Academic & Technical Background: Bachelor’s, Master’s, or PhD in Computer Science, AI, Machine Learning, or related fields.

  • Deployment Knowledge: Experience with cloud platforms (AWS, GCP, Azure) and MLOps pipelines

  • Programming Skills: Proficiency in Python, TensorFlow, PyTorch, or equivalent ML frameworks.

  • Data Science Proficiency: Ability to work with large-scale datasets, feature engineering, and model evaluation techniques.

  • Ethical AI: Understanding of AI fairness, transparency, and privacy-preserving machine learning.

Work Model & Expectations

  • Commitment: 10-15 hours per month.

  • Work Type: Remote

  • Location: Open to global applicants.

  • Compensation: Currently voluntary; early contributors will be prioritized for paid roles once funding is secured

Let’s work together.

If you're passionate about developing machine learning solutions that improve healthcare and education, apply today and help shape the future of ethical AI!