Senior ML Engineer — Production Underwriting & Infra

Kikoff Inc.; San Francisco (CA); On-site; USD 244,000 - 292,000; Full time

Job summary

Kikoff Inc. in the United States is seeking a Senior Machine Learning Engineer to build and operate ML infrastructure and models for underwriting and other financial services.

You will work with data scientists, software engineers, and product managers to deploy scalable ML solutions, monitor performance, and run experiments to optimize outcomes.

We value ownership, collaboration, and continuous learning, with a competitive base range and opportunities for impact at scale.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or related field; advanced degree preferred.
• Minimum of 3 years of experience in ML engineering with production deployments.
• Proficiency in Python or Ruby; strong CS fundamentals.
• Experience with TensorFlow or PyTorch; MLops and cloud/containerization experience.
• Ability to deploy scalable ML models and collaborate with cross-functional teams.

Responsibilities

• Design, build, and maintain ML infrastructure and data pipelines.
• Develop and deploy ML models for underwriting and financial services.
• Collaborate with data scientists, engineers, and product managers.
• Monitor model performance and drive continuous improvement.
• Lead A/B testing and experimentation; mentor junior engineers.

Skills

Python

Ruby

TensorFlow

PyTorch

AWS

GCP

Docker

Kubernetes

MLOps

Data pipelines

Statistical analysis

Problem solving

Communication

Education

Bachelor's degree in CS/Engineering/Math

Advanced degree preferred

Tools

Docker

Kubernetes

AWS

GCP

CI/CD tooling

Job description

Kikoff Inc. in the United States is seeking a Senior Machine Learning Engineer to build and operate ML infrastructure and models for underwriting and other financial services.

You will work with data scientists, software engineers, and product managers to deploy scalable ML solutions, monitor performance, and run experiments to optimize outcomes.

We value ownership, collaboration, and continuous learning, with a competitive base range and opportunities for impact at scale.