AI/ML Engineer-1

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