Staff Machine Learning Engineer

What You’ll Be Doing:

• Designing and implementing efficient and scalable machine learning pipelines, across multiple insurance use cases.
• Collaborating cross-functionally, serving as a technical lead for junior team members, providing mentorship and guidance to elevate team performance and technical knowledge.
• Ensuring production-grade deployment standards, emphasizing scalability, reliability, and compliance with insurance data handling policies, balancing rapid iteration with stability.
• Building reusable, modular infrastructure components and CI/CD pipelines for ML and LLM workloads, enabling rapid experimentation and seamless transition from research to production.
• Championing best practices in observability, testing, and monitoring of ML systems, establishing standards for model/data drift detection, logging, and automated rollback strategies.

What We Hope You Bring: 

• Proven experience as a Machine Learning Engineer or similar role (at least 8 years), with a strong focus on leveraging LLM models over the last 2 years.
• Expertise designing scalable and robust machine learning pipelines, both for classical machine learning systems and large language model applications.
• Knowledge of automating and monitoring ML workflows to ensure consistent model performance in production.
• Hands-on experience with cloud platforms, including deploying models, managing cloud resources, and using relevant APIs for data intake, storage, and processing
• Great communication skills with the ability to convey complex findings to non-technical audiences. 

 

Our cash compensation amount for this role is $210,000 to $250,000 annually. Final offer amounts are determined by multiple factors including candidate location, experience and expertise and may vary from the amounts listed above. Total compensation package does include stock options, benefits and additional perks. 

What You’ll Be Doing:

• Designing and implementing efficient and scalable machine learning pipelines, across multiple insurance use cases.
• Collaborating cross-functionally, serving as a technical lead for junior team members, providing mentorship and guidance to elevate team performance and technical knowledge.
• Ensuring production-grade deployment standards, emphasizing scalability, reliability, and compliance with insurance data handling policies, balancing rapid iteration with stability.
• Building reusable, modular infrastructure components and CI/CD pipelines for ML and LLM workloads, enabling rapid experimentation and seamless transition from research to production.
• Championing best practices in observability, testing, and monitoring of ML systems, establishing standards for model/data drift detection, logging, and automated rollback strategies.

What We Hope You Bring: 

• Proven experience as a Machine Learning Engineer or similar role (at least 8 years), with a strong focus on leveraging LLM models over the last 2 years.
• Expertise designing scalable and robust machine learning pipelines, both for classical machine learning systems and large language model applications.
• Knowledge of automating and monitoring ML workflows to ensure consistent model performance in production.
• Hands-on experience with cloud platforms, including deploying models, managing cloud resources, and using relevant APIs for data intake, storage, and processing
• Great communication skills with the ability to convey complex findings to non-technical audiences. 

 

Our cash compensation amount for this role is $210,000 to $250,000 annually. Final offer amounts are determined by multiple factors including candidate location, experience and expertise and may vary from the amounts listed above. Total compensation package does include stock options, benefits and additional perks.