job description
Join ManpowerGroup, a global leader in workforce solutions, as our next Senior AI/Machine Learning Ops (MLOps) Engineer in the vibrant tech hub of Bali, Indonesia. This is a unique opportunity to shape the future of AI-driven systems while enjoying the perfect work-life balance in one of the world's most desirable locations.
As an MLOps Engineer, you'll bridge the gap between data science and production, ensuring our machine learning models are scalable, reliable, and deliver real business value. You'll work with cutting-edge technologies to automate ML pipelines, optimize model performance, and deploy AI solutions that transform industries. This role is perfect for a hands-on engineer who thrives in collaborative environments and wants to make a tangible impact on AI adoption.
Bali offers an exceptional quality of life with its stunning landscapes, rich culture, and growing tech community. Enjoy competitive compensation, flexible work arrangements, and the opportunity to work with international teams while contributing to groundbreaking AI projects. Whether you're based in Canggu, Ubud, Denpasar, or Kuta, you'll find a supportive community of digital nomads and tech professionals.
If you're passionate about operationalizing AI and want to work where innovation meets paradise, we'd love to hear from you. Help us build the future of intelligent systems while enjoying Bali's world-class beaches, coworking spaces, and vibrant expat community.
Responsibility
- Design, build, and maintain scalable MLOps pipelines for model training, evaluation, and deployment
- Implement CI/CD workflows for machine learning systems to enable rapid, reliable model updates
- Optimize model performance through monitoring, A/B testing, and continuous improvement processes
- Collaborate with data scientists to productionize models while ensuring scalability and reliability
- Develop infrastructure as code (IaC) for ML environments using tools like Terraform or CloudFormation
- Implement model versioning, experiment tracking, and reproducibility frameworks
- Monitor model performance in production and implement automated retraining pipelines
- Ensure security and compliance of ML systems in production environments
Qualifications
- 5+ years of experience in software engineering with 2+ years in MLOps or ML engineering
- Strong proficiency in Python and experience with ML frameworks (TensorFlow, PyTorch, scikit-learn)
- Hands-on experience with cloud platforms (AWS preferred) and containerization (Docker, Kubernetes)
- Expertise in CI/CD pipelines and infrastructure as code (Jenkins, GitHub Actions, Terraform)
- Experience with ML monitoring tools (Prometheus, Grafana, MLflow) and model serving frameworks
- Solid understanding of data engineering concepts and distributed computing
- Familiarity with DevOps practices and tools (Linux, Bash, Ansible, etc.)
- Excellent problem-solving skills and ability to work in cross-functional teams