AI/ML Engineer
INFT Solutions inc
United States
18 days ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience required
1 year minimum
Working hours
Regular working hours
Job source
Tech stack
Application Programming Interfaces (APIs)
Artificial Intelligence
Amazon Web Services
Data Analysis
Microsoft Azure
Cloud Computing
Cloud Engineering
Databases
Continuous Integration
Data Cleansing
Fraud Prevention and Detection
Python (Programming Language)
+16 more
Machine Learning
NumPy
Tensorflow
Standard Sql
Azure Machine Learning
Google Cloud
Feature Engineering
Pytorch
Large Language Models
Model Validation
Generative AI
Pandas
Scikit Learn
Kubernetes
Machine Learning Operations
Docker
Job description
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., * 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.
Requirements
- 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 Google Cloud Platform.
- 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.
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