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Senior / Lead ML/AI Ops Engineer (P&C Insurance) Fully Remote | Full-Time Partnering with a Leading P&C Insurance Car...

Ai Machine Learning Data Science Mlops

Fully remote

This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Senior MLOps Engi...

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Are you excited about building software solutions around large, complex Machine Learning (ML) and Artificial Intellig...

Fulltime Ai Machine Learning Deep Learning

$138k - $239k · Senior Fully remote

A

Are you excited about building software solutions around large, complex Machine Learning (ML) and Artificial Intellig...

Fulltime Ai Machine Learning Deep Learning

$138k - $239k · Senior Fully remote

A

Are you excited about building software solutions around large, complex Machine Learning (ML) and Artificial Intellig...

Fulltime Ai Machine Learning Deep Learning

$138k - $239k · Senior Fully remote

A

Are you excited about building software solutions around large, complex Machine Learning (ML) and Artificial Intellig...

Fulltime Ai Machine Learning Deep Learning

$138k - $239k · Senior Fully remote

A

Are you excited about building software solutions around large, complex Machine Learning (ML) and Artificial Intellig...

Fulltime Ai Machine Learning Deep Learning

$138k - $239k · Senior Fully remote

A

Are you excited about building software solutions around large, complex Machine Learning (ML) and Artificial Intellig...

Fulltime Ai Machine Learning Deep Learning

$138k - $239k · Senior Fully remote

A

Are you excited about building software solutions around large, complex Machine Learning (ML) and Artificial Intellig...

Fulltime Ai Machine Learning Deep Learning

$138k - $239k · Senior Fully remote

A

Are you excited about building software solutions around large, complex Machine Learning (ML) and Artificial Intellig...

Fulltime Ai Machine Learning Deep Learning

$138k - $239k · Senior Fully remote

A

Are you excited about building software solutions around large, complex Machine Learning (ML) and Artificial Intellig...

Fulltime Ai Machine Learning Deep Learning

$138k - $239k · Senior Fully remote

A

Are you excited about building software solutions around large, complex Machine Learning (ML) and Artificial Intellig...

Fulltime Ai Machine Learning Deep Learning

$138k - $239k · Senior Fully remote

A

Are you excited about building software solutions around large, complex Machine Learning (ML) and Artificial Intellig...

Fulltime Ai Machine Learning Deep Learning

$138k - $239k · Senior Fully remote

A

Are you excited about building software solutions around large, complex Machine Learning (ML) and Artificial Intellig...

Fulltime Ai Machine Learning Deep Learning

$138k - $239k · Senior Fully remote

Selected role

Senior MLOps Engineer

James Search Group

Senior Full-time

Senior / Lead ML/AI Ops Engineer (P&C Insurance)

Fully Remote | Full-Time

Partnering with a Leading P&C Insurance Carrier

James Search Group is excited to be partnering with a forward-thinking P&C insurance carrier that is actively investing in the buildout of a centralized
Data & ML/AI function
. As part of this initiative, we are searching for a
Senior or Lead MLOps Engineer
to help scale and productionize a growing portfolio of machine learning and AI models that directly impact underwriting, claims, pricing, and customer experience.

This is a foundational role on a multidisciplinary team of Data Scientists, Engineers, and Analysts. You’ll play a key part in designing and maintaining the systems, workflows, and infrastructure that allow the team to deploy, monitor, and continuously improve ML/AI solutions in a robust and scalable way.

Office Locations (Optional Hybrid):

This is a remote-first position, but you can also work from one of the carrier’s multiple U.S. office locations

What You’ll Do:

Architect and build end-to-end MLOps pipelines for training, testing, deployment, and monitoring of machine learning models in production.
Implement model versioning, lineage, CI/CD for ML workflows, and containerization using modern DevOps and MLOps tools.
Collaborate with Data Scientists and ML Engineers to optimize model performance, reliability, and scalability.
Lead the adoption of best practices for model deployment, monitoring, governance, and retraining workflows.
Design infrastructure that supports real-time inference, batch scoring, and streaming pipelines.
Ensure ML systems meet high standards for security, reproducibility, observability, and compliance.

What You Bring:

5–8+ years of experience in ML/AI infrastructure, MLOps, or platform engineering.
Strong programming skills in Python and experience building production-grade ML systems.
Deep experience with MLOps tools and platforms such as MLflow, Airflow, GitHub Actions, Arize, Seldon, or SageMaker .
Solid understanding of containerization (e.g., Docker, Kubernetes ) and cloud services (e.g., AWS, GCP, Azure ).
Experience deploying and monitoring models at scale across various inference modalities (real-time, batch, streaming).
Familiarity with Databricks , dbt , and modern data orchestration tools.
Excellent problem-solving skills and ability to work cross-functionally with data science, engineering, DevOps, and security teams.
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field.

Bonus Points For:

Experience working in highly regulated environments like insurance or financial services .
Familiarity with model explainability, fairness auditing, or regulatory compliance in ML systems.
Exposure to Hex , Feature Stores , or monitoring frameworks like Evidently, WhyLabs, or Arize AI.
Passion for automation, observability, and reducing manual model management overhead.

What’s In It for You:

$135,000-$185,000 base salary
Performance-based bonus/variable compensation
Comprehensive benefits , including:
Medical, dental, and vision insurance
401(k) with company match
Generous PTO
Mental health & wellness support
Remote flexibility

This is a unique opportunity to shape the technical foundation of ML/AI operations at a modern insurance organization committed to innovation.

If you're passionate about building robust ML infrastructure and enabling scalable data science — let’s talk.

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