We are looking for an experienced Backend & ML Engineer to architect and build our core data processing infrastructure. This role requires deep technical expertise in high-performance backend systems, data engineering, and deploying optimized machine learning pipelines in production. If you have a strong background in Node.js, TypeScript, PostgreSQL, and ML model deployment, and you're passionate about designing scalable, efficient, and robust data architectures, we'd love to hear from you.

Role Overview

As a Backend & ML Engineer, you will be responsible for designing and implementing high-performance data processing pipelines, optimizing machine learning models, and developing scalable backend systems. You will work closely with infrastructure, data, and engineering teams to build robust solutions for insurance data processing, policy renewal predictions, and real-time lead matching.

Key Responsibilities

✅ Backend & Data Engineering

Architect and develop high-performance data processing pipelines for large-scale insurance data.
Optimize PostgreSQL databases (indexing, query performance tuning, and handling large datasets).
Implement type-safe APIs using Fastify and Zod with robust validation and error handling.
Develop and optimize real-time lead matching algorithms with configurable matching criteria.

✅ Machine Learning & Model Optimization

Build and enhance our policy renewal prediction engine, focusing on feature engineering and performance monitoring.
Deploy and optimize machine learning models in production environments.
Implement statistically rigorous A/B testing methodologies for model evaluation.
Develop metrics collection systems for ongoing model assessment and improvement.

✅ Infrastructure & Performance Optimization

Utilize Polars for high-performance data manipulation and transformation.
Implement Redis for caching strategies and event-driven architectures.
Ensure efficient containerization and orchestration using Docker and deployment best practices.
Optimize memory and CPU performance for data-heavy workloads.

✅ Collaboration & Deployment

Work closely with infrastructure teams on ML deployment strategies.
Implement CI/CD pipelines for automated testing and deployment of data-intensive applications.
Utilize Terraform for infrastructure-as-code deployments.

Technical Requirements

🔹 Backend Development

Expert in Node.js / TypeScript, with experience in clean architecture & domain-driven design.
Proficiency in Fastify and Zod for API development and validation.
Experience with Kysely for type-safe SQL query construction.

🔹 Database & Performance Optimization

Deep knowledge of PostgreSQL (indexing strategies, query tuning, large dataset handling).
Strong experience with Redis for caching and event-driven architecture.

🔹 Machine Learning & Data Processing

Proficient in Polars for high-performance data manipulation.
Experience deploying and optimizing ML models in production.
Strong understanding of A/B testing methodologies for evaluating model performance.

🔹 Infrastructure & Deployment

Experience with Docker for containerized deployments.
Hands-on experience with Terraform for infrastructure management.
Familiarity with CI/CD pipelines for automated testing and deployments.

🔹 Bonus Skills

Understanding of React/Next.js to support backend functionality in frontend applications.
Experience in predictive modeling and statistical analysis for data-driven decision-making.

Why Join Us?

🚀 Work on cutting-edge ML & backend engineering challenges

⚙️ Build scalable, high-performance data-driven solutions

💡 Collaborate with a skilled team in an innovative environment

🌍 Remote-friendly with growth opportunities

Does this sound like you? Apply now and be part of our journey in building intelligent and scalable data solutions!