Lead GenAI Engineer: LLMs, Pipelines & Strategy

Robotic Technologies Automation; Atlanta (GA); On-site; USD 150,000 - 190,000; Full time

Job summary

Robotic Technologies Automation in Atlanta, GA is seeking a senior Machine Learning Engineer with 8+ years of experience to design, build, and deploy Generative AI models (LLMs, diffusion models) for practical business applications. You will bridge cutting-edge research with user-facing solutions and communicate complex AI concepts to diverse stakeholders.

The role requires hands-on coding and strong collaboration with product, data science, and engineering teams, focusing on scalable GenAI

Qualifications

• 10+ years as ML Engineer with 1–2 years in Generative AI or NLP projects.
• Experience on AWS cloud platform and building production ML pipelines.

Responsibilities

• GenAI development: architect, fine-tune, and deploy LLMs and GenAI techniques.
• Production deployment: build scalable ML pipelines and GPU inference in cloud environments (AWS/GCP/Azure).
• Collaborate with product managers, data scientists, and engineers to translate requirements.
• Present AI methodologies and results to non-technical stakeholders and leadership.
• Model optimization: prompt engineering, adversarial testing, and efficient outputs.
• Keep up with GenAI research and incorporate into production systems.
• Coordinate with offshore teams on project deliverables.

Skills

Python

LLMs

GenAI

NLP

Communication

Problem solving

Education

Engineering degree in CS

ML certification

Tools

Docker

Kubernetes

CI/CD

GitHub Copilot

AWS SageMaker

AWS Bedrock

LangChain

Vector Databases

Knowledge graphs

Job description

Robotic Technologies Automation in Atlanta, GA is seeking a senior Machine Learning Engineer with 8+ years of experience to design, build, and deploy Generative AI models (LLMs, diffusion models) for practical business applications. You will bridge cutting-edge research with user-facing solutions and communicate complex AI concepts to diverse stakeholders.

The role requires hands-on coding and strong collaboration with product, data science, and engineering teams, focusing on scalable GenAI