We are looking for a MLOps engineer to join a fast growing InsurTech.

As one of the first MLOps engineers, you will be central to developing and maintaining the growing infrastructure to deploy machine learning at Waffle and have a great deal of exposure to the senior team.

Crucially, you will play a key role in developing products that will fundamentally change how data is utilized in the insurance industry. You will work directly with the Chief Data Officer and the Lead Engineer on a day-to-day basis to help shape the data practice and culture.

This is a US, remote first role.

About Waffle

Welcome to Waffle! We're not your typical insurance company. Born at MIT and raised in the heart of New York, we're a tribe of tech enthusiasts dedicated to reinventing insurance so that it works for everyone. Backed by global insurance giants and leading investors, we're the only platform worldwide where you can safeguard everything and everyone you love instantly. If you're ready to challenge the status quo, come join us at Waffle. Let's reshape the future of insurance—one bite at a time.

Key Responsibilities:

• Design and implement MLOps on the cloud with AWS
• Build CI/CD pipelines orchestration to assist engineering in maintaining our infrastructure and data reporting
• Work with the Chief Data Officer to review, refactor, optimize, containerize, and deploy advanced machine learning toolkits throughout our product life cycle
• Develop automated tests for validation and testing of machine learning models

Required Skills:

• Experience with MLOps Frameworks like Kubeflow, MLFlow, DataRobot, Airflow etc., experience with Docker and Kubernetes, OpenShift
• Experience optimizing and deploying machine learning models along with data pipelines
• Advanced knowledge of Python and knowledge of frameworks such as scikit-learn, Keras, PyTorch, Tensorflow, etc.
• Previous experience as a MLOps engineer or in a similar role
• Experience working in a startup or demonstrated ability to thrive in fast-paced environment
• Ability to understand tools used by data scientist and experience with software development and test automation
• Experience with AWS cloud services: EC2, Redshift

Bonus:

• Experience with data visualization tools (e.g. Tableau)
• Advanced knowledge in SQL Query Languages
• Experience with Generative AI deployment pipelines (e.g. LangChain)

Compensation and Benefits:
Base salary plus equity consistent with experience

• Salary: $90k - $120k
• Equity: 0.1% - 0.2%
• Healthcare Insurance included
• Waffles!

If interested, please apply here or reach out to [email hidden] with your interest.