Unspecified Salary Full Time
AI/ML Engineer-1
Job Description

New York City, New York 10010 Posted March 26th, 2026

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Job Type: Full Time

Job Category: IT

Job Description

Role- AI/ML Engineer

Location-Lebanon, NJ – 08833/ NY, NY – 10010(Onsite)

Full Time Employment

Role Overview

We are looking for a skilled AI/ML Engineer to design, build, and deploy scalable machine learning solutions. The ideal candidate will have strong experience in AWS ML ecosystem, MLOps, and production-grade model deployment, along with domain exposure in Insurance (Claims, Underwriting, Fraud Detection).

Key Responsibilities

Design and develop end-to-end machine learning pipelines for training, validation, and deployment

Build and manage ML workflows using Amazon SageMaker and AWS ML services

Implement MLOps best practices, including CI/CD pipelines for ML models

Deploy models as scalable inference endpoints and monitor performance in production

Containerize ML applications using Docker and orchestrate using Kubernetes (EKS preferred)

Collaborate with data scientists, data engineers, and business teams to translate requirements into ML solutions

Optimize models for performance, scalability, and cost-efficiency

Ensure proper versioning, monitoring, and governance of ML models

Required Skills & Qualifications

Strong experience with Amazon SageMaker and AWS ML services

Hands-on expertise in MLOps, including CI/CD for ML workflows

Experience building ML pipelines (training, validation, deployment)

Proficiency in model deployment and managing real-time/batch inference endpoints

Solid experience with Docker and containerization

Hands-on experience with Kubernetes and Amazon EKS

Programming experience in Python and ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn)

Experience with version control systems (Git) and automation tools

Understanding of data engineering concepts and cloud architecture

Preferred Qualifications

Experience in the Insurance domain, including:

Claims processing automation

Underwriting risk models

Fraud detection systems

Familiarity with streaming/data pipeline tools (e.g., Kafka, Spark)

Knowledge of monitoring tools for ML systems (e.g., model drift, performance tracking)

Experience with Infrastructure as Code (Terraform/CloudFormation)

Required Skills

DEVOPS ENGINEER

SENIOR EMAIL SECURITY ENGINEER