job description
Are you passionate about leveraging AI to revolutionize software development? Join our dynamic team as an AI MLOps Engineer and play a pivotal role in creating and testing innovative AI solutions that enhance productivity and drive technological advancements. Based in the vibrant regions of Bali, this role offers a unique opportunity to work in a collaborative environment while enjoying the island's inspiring lifestyle.
As an AI MLOps Engineer, you will bridge the gap between AI research and production, ensuring seamless integration and deployment of machine learning models. Your expertise will contribute to optimizing software development processes, automating workflows, and delivering cutting-edge AI-driven solutions.
If you thrive in a fast-paced, innovative setting and are eager to make a tangible impact, we invite you to apply and be part of our mission to transform the future of technology.
Responsibility
- Design, develop, and deploy scalable AI/ML models and pipelines to enhance software development productivity.
- Collaborate with cross-functional teams to integrate AI solutions into existing systems and workflows.
- Implement MLOps best practices, including CI/CD pipelines, model versioning, and monitoring.
- Optimize and fine-tune machine learning models for performance, scalability, and efficiency.
- Automate data preprocessing, feature engineering, and model training processes.
- Ensure the reliability, security, and compliance of AI systems in production environments.
- Conduct experiments and A/B testing to validate the effectiveness of AI-driven solutions.
- Stay updated with the latest advancements in AI, MLOps, and software development to drive continuous improvement.
Qualifications
- Bachelor's or Master's degree in Computer Science, Artificial Intelligence, or a related field.
- Proven experience as an MLOps Engineer, AI Engineer, or similar role, with a strong portfolio of AI/ML projects.
- Proficiency in programming languages such as Python, and frameworks like TensorFlow, PyTorch, or scikit-learn.
- Experience with MLOps tools and platforms, including MLflow, Kubeflow, or similar.
- Strong understanding of cloud platforms (AWS, GCP, or Azure) and containerization technologies (Docker, Kubernetes).
- Familiarity with data engineering, ETL processes, and big data technologies.
- Excellent problem-solving skills and the ability to work in a collaborative, agile environment.
- Strong communication skills and the ability to explain complex AI concepts to non-technical stakeholders.