Work Based Learning Coordinator

Universal Charter Schools; Philadelphia (Philadelphia County); On-site; USD 120,000 - 180,000; Full time

Benefits offered by this job

Annual discretionary bonus

Up to 11% pension contributions

Hybrid working + flexible hours

25 days annual leave + bank holidays +

Health & wellbeing + virtual GP

Career development and mentoring

Inclusive culture + employee networks

Share investment options

Job summary

Intact Insurance is hiring a Machine Learning Engineer to design and deploy production-grade ML systems. You will partner with data scientists and engineers to shape the ML roadmap, build scalable pipelines, and deliver impactful solutions across the business.

You’ll drive feature engineering, model training, real-time and batch deployments, and robust monitoring. Strong Python/PySpark/SQL skills and cloud experience are essential.

Qualifications

• Experience with ML platforms including Databricks, MLflow, Delta Lake, and cloud environments.
• Proficient in Python, PySpark, and SQL, following production coding best practices.
• Understanding of data, distributed ML pipelines, and model deployment patterns, including monitoring, drift detection, and lifecycle operations.
• Exposure to CI/CD, containerisation, and API integration, with the ability to build scalable, production-ready ML systems.
• Comfortable working technically while communicating effectively with Data Scientists, stakeholders, and cross-functional teams.

Responsibilities

• Build and automate ML pipelines for feature engineering, model training, and model scoring using Python, PySpark, Databricks, and MLflow.
• Productionise Data Science models, converting notebooks into modular, tested, production-ready code.
• Deploy models into batch and real-time environments, managing versioning, promotion, rollback, and scheduled workflows via MLflow and APIs.
• Implement monitoring and observability, including data and model drift detection, performance alerts, logging, and automated retraining.
• Collaborate with Data Engineering and Platform teams on CI/CD integration, pipeline performance, compute optimisation, and secure deployment patterns.
• Maintain engineering standards, ensuring high-quality testing, documentation, code quality, reproducibility, and operational reliability.

Skills

Databricks

MLflow

Python

PySpark

SQL

CI/CD

Containerization

API integration

Data pipelines

Job description

Machine Learning Engineer

Job Title Machine Learning Engineer Reference UK003413 Town Multiple Office Locations Business Line IS & Change

Intact Insurance is the new name for RSA in the UK, Ireland, and across Europe. It’s a new name and a new way to do business. Backed by global expertise and a commitment to service that feels different, we’re focused on making insurance simpler, faster, and more responsive.

Shape the future:

We’re leading a transformation in insurance helping people, businesses and society prosper in good times and be resilient in bad times. When you join us, you’re not just taking a job, you’re stepping into a career where you can make a real difference.

Grow with us:

We’re customer-driven, community-focused, and committed to helping our people grow. Whether you’re early in your journey or bringing years of experience, we’ll support you with the tools, flexibility, and opportunities to thrive.

Win as a Team:

We’re looking for a Machine Learning Engineer to help build and run production-ready ML systems that make a real impact across the business. You’ll work closely with Data Scientists and engineering teams, shaping the ML roadmap, developing scalable solutions, and driving innovation while growing your career.

You’ll make an impact by:

• Build and automate ML pipelines for feature engineering, model training, and model scoring using Python, PySpark, Databricks, and MLflow.
• Productionise Data Science models, converting notebooks into modular, tested, production-ready code.
• Deploy models into batch and real-time environments, managing versioning, promotion, rollback, and scheduled workflows via MLflow and APIs.
• Implement monitoring and observability, including data and model drift detection, performance alerts, logging, and automated retraining.
• Collaborate with Data Engineering and Platform teams on CI/CD integration, pipeline performance, compute optimisation, and secure deployment patterns.
• Maintain engineering standards, ensuring high-quality testing, documentation, code quality, reproducibility, and operational reliability.

Your skills and experience:

• Experience with ML platforms including Databricks, MLflow, Delta Lake, and cloud environments.
• Proficient in Python, PySpark, and SQL, following production coding best practices.
• Understanding of data, distributed ML pipelines, and model deployment patterns, including monitoring, drift detection, and lifecycle operations.
• Exposure to CI/CD, containerisation, and API integration, with the ability to build scalable, production-ready ML systems.
• Comfortable working technically while communicating effectively with Data Scientists, stakeholders, and cross-functional teams.

Why You’ll Love It Here:

Being part of our team means you’ll have the support and freedom to bring your best self to work each day. As a permanent member, here’s what you can look forward to

• Annual discretionary bonus
• Up to 11% pension contributions
• Hybrid working + flexible hours
• 25 days annual leave + bank holidays + buy/sell options
• Health & wellbeing + virtual GP
• Career development and mentoring
• Inclusive culture + employee networks
• Share investment options

Our DEI Commitment:

We celebrate individuality and believe our differences make us stronger. We’re proud to foster a culture where everyone feels respected, valued, and empowered to thrive.
As an Equal Opportunity and Disability Confident Employer, we ensure fair consideration for all applicants and offer interviews to all disabled candidates who meet the essential criteria.
We understand that everyone’s circumstances are different and are happy to explore flexible working options such as reduced hours or job shares to support work–life balance.
If you meet the core criteria but not every requirement, we’d still love to hear from you. Let’s explore how this role could support your next career step. If you need adjustments during the recruitment process, just let us know we’re here to support you.

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