🛠 Tech Stack

💼 About This Role

You'll design and deploy machine learning pipelines and APIs for a leading catastrophe property insurer. Your work will directly optimize orchestration and model delivery, ensuring fast and reliable production deployment. This role offers the stability of a profitable company with startup-like entrepreneurial spirit.

🎯 What You'll Do

• Design and implement scalable data pipelines for ML models.
• Develop prediction pipelines for production integration.
• Create APIs and microservices between ML models and software.
• Manage model deployment strategies with monitoring and logging.

📋 Requirements

• 5-7 years experience as MLOps Engineer or similar role.
• Proficiency in cloud platforms (AWS, Azure, GCP) and containerization.
• Experience with orchestration tools like Airflow, Kubeflow, or MLflow.
• Experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-Learn.

✨ Nice to Have

• Experience with cost-saving infrastructure strategies.
• Strong problem-solving skills and independence.
• Excellent cross-functional communication skills.

🎁 Benefits & Perks

• 🏖️ Remote flexibility (distributed workforce).
• 💰 Competitive compensation (estimated).
• 🚀 Stable company with years of underwriting profits.
• 💡 Innovative data culture across Data Science, BI, and Data Management.

📨 Hiring Process

Estimated timeline: 2-3 weeks · AI estimate

1. 1Recruiter Call· 30 min
2. 2Technical Interview· 60 min
3. 3Hiring Manager Interview· 45 min