A globally recognised tech company that values freedom of creation, embraces diversity and fosters an open, learning, and sharing work environment. They integrates the concept of 'Creative AI' into product development, using Generative AI, Machine Learning, Data Analytics and other technologies to create easy-to-use image editing products for users. Their main product has already achieved over 260 million downloads worldwide with a stable user base of 15 million per month.
Salary: Competitive and based on experience
Location: Taipei
Keywords: MLOps, Engineer, Machine Learning, Data Pipelines, Automation, Collaboration
Our client is a globally recognised tech company, known for their commitment to creating meaningful products that make the world more fun and creative. They are currently seeking an MLOps Engineer to join their dynamic team in Taipei. In this role, you will play a pivotal part in designing, implementing, and maintaining robust machine learning platforms and data pipelines. You will ensure smooth deployment, scaling, and monitoring of models in production environments. This is an exciting opportunity to work on high-impact projects that reach millions of users worldwide.
- Design, implement and maintain machine learning platforms and data pipelines
- Ensure seamless deployment, scaling, and monitoring of models in production environments
- Work on high-impact projects that reach millions of users worldwide
What you'll do:
As an MLOps Engineer, your role will be integral to the success of our client's innovative tech initiatives. You will design, implement and maintain machine learning platforms and data pipelines while ensuring seamless deployment, scaling, and monitoring of models in production environments. Your expertise will be crucial in setting up monitoring systems for deployed models and tracking key metrics. You will also collaborate closely with ML developers to ensure model performance is maintained in production.
- Design, implement and maintain machine learning platform and data pipelines
- Ensure seamless deployment, scaling, and monitoring of models in production environments
- Set up monitoring systems for deployed models and track key metrics
- Apply and share software engineering best practices within the context of machine learning
- Collaborate with ML developers to ensure model performance is maintained in production
- Work with software engineers to integrate ML systems into the broader application stack
- Accelerate machine learning development, evaluation, and integration speed through automation of workflows, tools, and processes
What you bring:
The ideal candidate for the MLOps Engineer position brings strong programming skills in Python along with proficiency in containerization tools such as Docker or Kubernetes. You have experience working with backend servers and APIs like FastAPI or Django. Your background includes working with machine learning frameworks like PyTorch or TensorFlow. Experience with MLOps tools such as Kubeflow, MLflow, TFX and monitoring tools like Prometheus or Grafana will be highly beneficial. A solid understanding of data engineering concepts including ETL pipelines, data lakes, and data warehouses is also desirable.
- Strong programming skills in Python
- Proficiency with containerization tools (Docker, Kubernetes) and cloud platforms (GCP, AWS, Azure)
- Experience working with backend servers and APIs (e.g., FastAPI, Django)
- Experience with machine learning frameworks (PyTorch, TensorFlow)
- Experience with MLOps tools (Kubeflow, MLflow, TFX)
- Experience with monitoring tools (Prometheus, Grafana) and logging frameworks
- Knowledge of data engineering concepts (ETL pipelines, data lakes, data warehouses)
What's next:
Ready to take your career to the next level with this exciting MLOps Engineer role? Don't wait!
Apply today by clicking on the link!
