Senior AI/ML Engineer: Generative AI, MLOps & AWS

Robotic Technologies Automation; Pennsylvania; On-site; USD 140,000 - 190,000; Full time

Job summary

Robotic Technologies Automation seeks a senior AI/ML engineer to design and deploy production-grade ML systems in the cloud. You will build LLM-based applications with RAG, implement secure tool orchestration, and manage model lifecycles using AWS SageMaker, Glue, Bedrock and Lambda.

Collaborating with product owners and stakeholders, you will craft scalable data pipelines, apply MDLC best practices, and advance testing, monitoring, and reproducibility across teams while maintaining high

Qualifications

• Experience designing and deploying production-grade ML systems.
• Building scalable data pipelines and ML workflows.
• Managing model lifecycle in cloud environments.
• Proficiency in Python and ML frameworks (TensorFlow, PyTorch, scikit-learn).
• Strong AWS ML stack knowledge and related tooling.

Responsibilities

• Implement agentic frameworks (LangGraph, AutoGen) and MCP for orchestration.
• Develop LLM-based applications with RAG and evaluation frameworks.
• Deploy models using SageMaker pipelines, ECS/ECR, Lambda; manage CI/CD and monitoring.
• Collaborate with product and stakeholders to align solutions with objectives.
• Ensure security, reproducibility, and scalability across ML projects.

Skills

AI/ML engineering

Data engineering

MLOps

Production ML systems

Data pipelines

Model lifecycle

Python

Software engineering

Security & authentication

Communication & collaboration

Ambiguity handling

Education

Bachelor's degree in Computer Science/Engineering

Master’s preferred

Tools

AWS SageMaker

AWS Glue

AWS Bedrock

AWS Lambda

Docker

Kubernetes

TensorFlow

PyTorch

Scikit-learn

React UI

GraphDB

Git

CI/CD

Job description

Robotic Technologies Automation seeks a senior AI/ML engineer to design and deploy production-grade ML systems in the cloud. You will build LLM-based applications with RAG, implement secure tool orchestration, and manage model lifecycles using AWS SageMaker, Glue, Bedrock and Lambda.

Collaborating with product owners and stakeholders, you will craft scalable data pipelines, apply MDLC best practices, and advance testing, monitoring, and reproducibility across teams while maintaining high