Sr. Machine Learning Ops Engineer

Our mission at Sense is to make all homes intelligent by keeping people informed about what's happening in their homes, and helping to make homes safer, more efficient, and more reliable.

At Sense, we are serious about having a real impact on climate change.

The technology team at Sense is looking for an experienced ML Operations Engineer to help the data science team scale and to deploy, monitor, and maintain machine learning models in production.

Responsibilities 

• Design, build, and maintain model training and serving infrastructure for CI/CD
• Collaborate with data scientists and data engineers to improve productivity by increasing automation for model training and experimentation workflows
• Provide technical leadership to data engineers
• Support annotation and ground truth collection through tool improvement and automation
• Champion best practices for data science software development processes and serve as architect for shared data science software libraries
• Work with the infrastructure guild to upgrade and patch libraries; maintain and optimize pipelines
• Responsible for ensuring data science production software is robust and scalable
• Identify and implement cost savings; monitor and manage costs

Qualifications

• 5+ years of experience designing, building, and maintaining production AI/ML applications
• Strong programming skills (Python, C, etc.) 
• Experience with ML libraries (PyTorch, scikit-learn, Tensorflow)
• Cloud experience (AWS preferred)
• Experience with frameworks such as MLFlow, Kubeflow, Airflow, Docker, etc.
• Strong communication and collaboration skills 
• Must be authorized to work in the U.S.