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Machine Learning Engineering Lead

3 weeks ago

Johor Bahru, Johor, Malaysia Presgo Gateways Full time

Key Responsibilities:

  1. Design, Develop, and Deploy AI-driven Applications: Create innovative AI-driven applications, models, and algorithms that drive business growth and customer satisfaction.
  2. Lead AI Research and Development Efforts: Drive research and development initiatives to improve existing systems and create novel AI-powered solutions.
  3. Optimize Machine Learning Models: Enhance performance, scalability, and accuracy of ML models through rigorous testing and optimization.
  4. Collaborate with Cross-functional Teams: Work closely with software developers, data scientists, and product managers to integrate AI solutions into various platforms.
  5. Manage Large-scale Datasets: Oversee the management and fine-tuning of large datasets for training AI models.
  6. Stay Up-to-date with Industry Advancements: Maintain expertise in the latest AI, ML, and deep learning technologies.
  7. Ethics, Security, and Compliance: Ensure AI systems adhere to ethical guidelines, security policies, and data privacy regulations.

Requirements:

  1. Advanced Degree: Master's degree or PhD in Computer Science, Artificial Intelligence, Machine Learning, Mathematics, or a related field.
  2. Experience: Bachelor's degree in Computer Science, Artificial Intelligence, Machine Learning, Mathematics, or a related field with minimum 5 years' experience, or equivalent combination of education and experience.
  3. Proven Experience: Demonstrated experience in AI/ML model development and deployment.
  4. Technical Skills: Strong proficiency in Python, TensorFlow, PyTorch, Keras, Scikit-learn, or similar frameworks.
  5. NLP and Computer Vision: Experience with NLP, computer vision, reinforcement learning, and deep learning techniques.
  6. Cloud Platforms: Knowledge of cloud platforms (AWS, GCP, Azure) for AI model deployment.
  7. MLOps and Automation: Hands-on experience with AI-driven automation, neural networks, and large-scale data processing.
  8. Familiarity with MLOps: Familiarity with MLOps, containerization (Docker, Kubernetes), and CI/CD pipelines is a plus.
  9. Communication Skills: Strong analytical, problem-solving, and communication skills.
  10. Basic Operations Research: Basic knowledge of operations research and/or causal theory is a big plus.
  11. Leadership Abilities: Ability to work in a fast-paced environment and lead AI initiatives effectively.