AIML Engineer
Job Location:
Jersey, NJ - USA
Monthly Salary:
Not provided by the employer
Posted:
16 September 2026 (5 days ago)
Application Deadline:
14 December 2026
Vacancies:
1 Vacancy
Job Summary
Job Summary
We are looking for an AI/ML Engineer with strong Insurance domain experience to design develop and deploy machine learning and AI solutions for insurance-related business problems. The candidate will work with business and technical teams to build predictive models automate processes analyze insurance data and improve decision-making.
Key Responsibilities
- Develop and implement Machine Learning and AI models for insurance use cases.
- Work with large and complex insurance datasets to identify patterns and insights.
- Build predictive models for areas such as claims underwriting risk assessment fraud detection and customer analytics.
- Perform data preprocessing feature engineering model training evaluation and optimization.
- Develop and maintain ML pipelines for model deployment and monitoring.
- Collaborate with Data Scientists Data Engineers Business Analysts and Insurance SMEs.
- Deploy AI/ML solutions into production environments and troubleshoot model-related issues.
- Apply NLP Generative AI or other AI techniques where applicable.
- Ensure models are scalable reliable and aligned with business requirements.
- Document models processes and technical solutions.
Required Skills
- 7 years of experience in AI/ML Engineering Machine Learning or Data Science.
- Strong experience with Python and ML libraries such as Scikit-learn Pandas NumPy TensorFlow or PyTorch.
- Experience with Machine Learning algorithms predictive modeling and statistical techniques.
- Experience with data preprocessing feature engineering and model evaluation.
- Knowledge of ML deployment APIs and MLOps concepts.
- Experience working with SQL and databases.
- Good understanding of cloud platforms such as AWS Azure or GCP.
- Strong Insurance domain experience is required.
Insurance Domain Experience
Experience with one or more of the following is preferred:
- Property & Casualty (P&C)
- Life Insurance
- Health Insurance
- Claims Processing
- Underwriting
- Risk Assessment
- Fraud Detection
- Policy Management
- Premium/Pricing Analytics
- Customer/Agent Analytics
Preferred Skills
- Experience with Generative AI / LLMs / NLP.
- Knowledge of MLOps and CI/CD.
- Experience with Docker/Kubernetes.
- Experience with cloud-based AI/ML services.
- Strong communication and problem-solving skills.