Role overview
**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.