Staff Machine Learning Engineer

What You'll Be Doing:

• Design and implement scalable machine learning pipelines, serving prompt engineering workflows to enhance scalability and efficiency in submission intake processes across multiple insurance use cases.
• Collaborate cross-functionally, serving as a technical lead for mid and senior team members, providing mentorship and guidance to elevate team performance and technical knowledge.
• Ensure production-grade deployment standards, emphasizing scalability, reliability, and compliance with insurance data handling policies, balancing rapid iteration with stability.
• Build reusable, modular infrastructure components and CI/CD pipelines for ML and LLM workloads, enabling rapid experimentation and seamless transition from research to production.
• Champion best practices in observability, testing, and monitoring of ML systems, establishing standards for model/data drift detection, logging, and automated rollback strategies.
• Partner with Data Science leaders to shape the vision and direction of MLOps at Federato and the future of our products

Who We Hope You Are:

• Proven experience as a Machine Learning Engineer or similar role (at least 7 years), with a strong focus on pipelining LLM models over the last 2 years.
• Proven experience in designing scalable and robust machine learning pipelines, both for classical machine learning and large language models (LLMs) along with familiarity with open-source models is a plus.
• Experience in building scalable ML pipelines using tools such as Kubeflow. 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. 
• Experience leading a team for high-visibility / high-impact projects 
• Proven record of influencing and executing ML product vision

 

$210,000 - $250,000 a year
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:

• Design and implement scalable machine learning pipelines, serving prompt engineering workflows to enhance scalability and efficiency in submission intake processes across multiple insurance use cases.
• Collaborate cross-functionally, serving as a technical lead for mid and senior team members, providing mentorship and guidance to elevate team performance and technical knowledge.
• Ensure production-grade deployment standards, emphasizing scalability, reliability, and compliance with insurance data handling policies, balancing rapid iteration with stability.
• Build reusable, modular infrastructure components and CI/CD pipelines for ML and LLM workloads, enabling rapid experimentation and seamless transition from research to production.
• Champion best practices in observability, testing, and monitoring of ML systems, establishing standards for model/data drift detection, logging, and automated rollback strategies.
• Partner with Data Science leaders to shape the vision and direction of MLOps at Federato and the future of our products

Who We Hope You Are:

• Proven experience as a Machine Learning Engineer or similar role (at least 7 years), with a strong focus on pipelining LLM models over the last 2 years.
• Proven experience in designing scalable and robust machine learning pipelines, both for classical machine learning and large language models (LLMs) along with familiarity with open-source models is a plus.
• Experience in building scalable ML pipelines using tools such as Kubeflow. 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. 
• Experience leading a team for high-visibility / high-impact projects 
• Proven record of influencing and executing ML product vision

 

$210,000 - $250,000 a year
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.