AI/ML Engineer

Ethereum Technologies; Pennsylvania; On-site; USD 150,000 - 210,000; Full time

Job summary

Ethereum Technologies is seeking a senior AI/ML engineer to design and deploy production-grade ML systems in a US-based environment. You will build scalable data pipelines, manage model lifecycles in AWS, and implement agentic frameworks for secure tool orchestration while collaborating with product owners and business partners.

You will leverage TensorFlow, PyTorch, and Scikit-learn, work with AWS SageMaker/Glue/Bedrock/Lambda, and apply MDLC best practices.

Qualifications

• Bachelor’s or higher in CS/Engineering (Master’s preferred).
• 6+ years in AI/ML engineering, data engineering, and MLOps.
• Designing and deploying production-grade ML systems.
• Building scalable data pipelines and ML workflows.
• Managing model lifecycle in cloud environments.
• Proficient in Python and ML frameworks (TF, PyTorch, Sklearn).
• Strong AWS ML Stack experience (SageMaker, Glue, Bedrock, Lambda).
• GenAI model development with RAG.
• Agentic frameworks (LangGraph, AutoGen) and MCP orchestration experience.
• Knowledge of React UI, GraphDB, and GenAI model evaluation.
• CI/CD, Docker, Kubernetes; software engineering fundamentals.
• Familiar with MDLC and reproducibility practices.
• Strong communication and cross-team collaboration.
• Ability to thrive amid ambiguity at scale.

Responsibilities

• Implement agentic frameworks (LangGraph/AutoGen) and MCP for secure tool orchestration.
• Develop LLM-based applications with RAG, structured output, and evaluation frameworks.
• Deploy models using AWS SageMaker pipelines, ECS/ECR, and Lambda; manage CI/CD and monitoring.
• Integrate Okta/JWT for API authentication and enforce token validation.
• Deliver artifacts required by MDLC (Model Documents, Data Dictionary, Monitoring Plan).
• Collaborate with PO and business stakeholders to align solutions with objectives.

Skills

Python

ML engineering

Data pipelines

MLOps

Cloud environments

Security

Communication

Ambiguity handling

Education

Bachelor's degree in Computer Science/Engineering

Master's degree preferred

Tools

TensorFlow

PyTorch

Scikit-learn

AWS SageMaker

AWS Glue

AWS Bedrock

AWS Lambda

Docker

Kubernetes

Git

Job description

US Citizen, Green Card, H-1B, OPT-EAD, CPT, Other

• Agentic AI & MCP Integration: Implement agentic frameworks (e.g., LangGraph, AutoGen) and Model Context Protocol (MCP) for secure tool orchestration.
• Generative AI Development: Build LLM-based applications with RAG, structured output, and evaluation frameworks.
• AWS ML Engineering: Deploy models using SageMaker pipelines, ECS/ECR, Lambda; manage CI/CD and monitoring.
• Security & Identity: Integrate Okta/JWT token for API and service authentication; enforce token validation and claims.
• Governance : Deliver artifacts required by MDLC/MPLC (Model Documents, Data Dictionary, Monitoring Plan).
• Collaboration: Partner with PO, and business stakeholders to align solutions with objectives.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or related field (Master’s preferred).
• 6+ years of experience across Artificial Intelligence (AI) / Machine Learning (ML) engineering, data engineering, and MLOps implementation, including:
• Designing and deploying production-grade ML systems.
• Building scalable data pipelines and ML workflows.
• Managing model lifecycle in cloud environments.
• Proficient in Python and familiar with ML frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• Strong understanding and experience in AWS Machine Learning Stack including:
• AWS SageMaker
• AWS Glue
• AWS Bedrock
• AWS Lambda Functions
• Experience with Generative AI model development builing LLM based applications with RAG.
• Experience implementing agentic frameworks (e.g., LangGraph, AutoGen) and Model Context Protocol (MCP) for orchestration.
• Knowledge of React UI, GraphDB, and GenAI model performance evaluation
• Experience with CI/CD, containerization (e.g., Docker), and orchestration tools (e.g., Kubernetes).
• Solid grasp of software engineering principles including testing, version control (e.g., Git), and security.
• Familiarity with the Machine Learning Development Lifecycle (MDLC) and best practices for reproducibility and scalability.
• Strong communication and collaboration skills, with experience working across technical and business teams.
• Ability to anticipate ambiguity and devise scalable solutions to address it.

We are an equal opportunity employer. All aspects of employment including the decision to hire, promote, discipline, or discharge, will be based on merit, competence, performance, and business needs. We do not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, national origin, citizenship/ immigration status, veteran status, or any other status protected under federal, state, or local law.