MLOps Engineer

About Us: We are a profitable and growing company, originating in Silicon Valley and now headquartered in Taiwan. We combine intuitive design with Creative AI tech to create inspiring products for millions of people worldwide.
We offer a fun, creative, and international workplace with competitive compensation, stock options, flexible hybrid work, free lunch, and more.
Ready to make a big impact with a talented team? Come create with us.
About the Role: At PicCollage, our Machine Learning, Algorithms & Data (MLAD) team thrives on solving complex challenges with elegance and scale. As a MLOps Engineer, you’ll be at the heart of this—designing and building robust platforms and pipelines that make it seamless to develop, deploy, and monitor ML models used by millions worldwide.You’ll collaborate closely with a team of like-minded experts who love sharing their deep domain knowledge, working together to bring cutting-edge AI research into real-world products. With a culture that champions continuous learning (yes, we sponsor trips to world-renowned conferences like CVPR), you’ll grow as you help deliver high-impact innovations—fast, reliable, and at scale.This role bridges the gap between ML engineers and product managers, empowering teams to integrate models effortlessly into applications while setting best practices for MLOps across the company. If you’re excited about solving interesting puzzles, automating workflows, and scaling ML systems for global reach—this is your place.

What You'll Do:

• Design, implement and maintain machine learning platform and data pipelines, ensuring seamless deployment, scaling, and monitoring of models in production environments.
• Set up monitoring systems for deployed models and tracking key metrics.
• Apply and share software engineering best practices within the context of machine learning.
• Collaborate with ML engineers to ensure model performance is maintained in production and 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 to enhance collaboration and efficiency.

What We’re Looking For: (Key Skills)

• Proficiency in Python, with solid software engineering fundamentals.
• Hands-on experience designing and building backend APIs or services with frameworks like FastAPI, Django, or similar.
• Experience building and operating containerized applications using Docker, with hands-on expertise in managing Kubernetes clusters.

Nice-To-Haves:

• Experience with cloud platforms such as GCP, AWS, or Azure.
• 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).
• Understand and apply AI tools into your workflow.