Senior MLOps Machine Learning Engineer

Strive Solutions; Chicago (IL); On-site; USD 140,000 - 210,000; Full time

Job summary

Strive Solutions in Chicago, IL seeks a Senior AI Engineer to design, build, and deploy scalable AI/ML solutions for the Insurance industry. You will drive model development to improve underwriting, claims, fraud detection, and customer experiences.

In this role you will develop production-grade AI/ML models, collaborate with data scientists and engineers, deploy models in cloud-based systems, and ensure reliability, fairness, and regulatory compliance while mentoring junior engineers and

Qualifications

• Production AI/ML experience in real-world systems.
• Experience with deployment, reliability, and MLOps practices.
• Ability to evaluate and improve model fairness and regulatory compliance.
• Strong collaboration across data science, engineering, and business teams.
• Mentorship experience and ability to lead technical initiatives.

Responsibilities

• Develop production-grade AI/ML models and features.
• Collaborate with data scientists and engineering teams.
• Integrate and deploy models into cloud-based systems.
• Ensure model reliability, fairness, and compliance.
• Mentor junior team members and promote engineering best practices.
• Drive MLOps standards for repeatable deployments.
• Partner with business stakeholders to translate data insights into measurable impact.

Skills

Production AI/ML experience

Deployment & MLOps

Fairness & compliance

Cross-functional collaboration

Mentorship & technical leadership

Job description

Senior AI Engineer to design, build, and deploy scalable AI/ML solutions for the Insurance industry. Drive model development that improves underwriting, claims, fraud detection, and customer experiences.

Key Responsibilities

• Develop production-grade AI/ML models and features.
• Collaborate with data scientists and engineering teams.
• Integrate and deploy models into cloud-based systems.
• Ensure model reliability, fairness, and compliance.
• Mentor junior team members and promote engineering best practices.
• Drive MLOps standards for repeatable, maintainable deployments.
• Partner with business stakeholders to translate data insights into measurable impact.

Qualifications & Skills

• Strong AI/ML engineering experience with production systems.
• Expertise in deployment, reliability, and MLOps practices.
• Ability to evaluate and improve fairness and compliance.
• Collaboration skills across data science, engineering, and business teams.
• Mentorship experience and technical leadership.