MLOps Engineer [Archived]

As an MLOps Engineer, you will play a key role in designing, implementing, and maintaining robust machine learning platforms and data pipelines, ensuring smooth deployment, scaling, and monitoring of models in production. You will drive automation to accelerate the development, evaluation, and integration of machine learning models, improving collaboration and overall efficiency. In addition to optimizing production environments, you will act as a bridge between machine learning developers and software engineers, ensuring seamless integration of ML systems into applications. You will also share best practices for MLOps and have the opportunity to work on high-impact projects that reach millions of users, as well as help bring innovative new applications to market.

Responsibilities:

• 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 developers 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.

Qualifications:

• Strong programming skills in Python.
• Proficiency with containerization tools (Docker, Kubernetes) and cloud platforms (GCP, AWS, Azure; expertise in at least one).
• Experience working with backend servers and APIs (e.g., FastAPI, Django, or similar frameworks).
• 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).

Flexible Work Time & Remote Work 彈性上下班時間 & 遠端工作

Maker Time 每週一天 Maker Time，不進行不必要的會議和討論

Team Activities and Workshops 各式活動與學習機會 (技術分享、Design Demo, Hack Days等）

Fun, Creative & International 雙語工作環境，團隊成員來自世界各地

Free Lunch and Dinner in the Office 辦公室內團隊午餐晚餐

Sports Classes in Office/Online 和同事一起起來動一動

PicCafe 健康零食水果，永遠餵飽你的胃

Awesome & Fun Office 有趣舒適大稻埕風的辦公室