Senior Python AI/ML Engineer - GenAI, MLOps & Pipelines

Kforce Inc; Coppell (TX); On-site; USD 140,000 - 230,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401(k) plan

Paid time off

Job summary

Kforce Inc. in Coppell, TX seeks a Senior Python AI/ML Engineer to design, develop, test, and deploy enterprise AI/ML solutions with strong emphasis on Python and API engineering.

You will build end-to-end pipelines, implement MLOps practices, and integrate RAG and large language models into enterprise applications. The role covers data engineering, cloud-native deployments on AWS/Azure/GCP, and robust CI/CD using tools like Jenkins, GitHub Actions, Docker, and Kubernetes.

Qualifications

• 8-12 years of software engineering experience with substantial Python development.
• Production experience designing and deploying AI/ML solutions.
• Strong understanding of ML algorithms and MLOps principles.

Responsibilities

• Design, develop, test, and deploy ML/Generative AI solutions for enterprise use cases.
• Build end-to-end AI/ML pipelines including data ingestion, feature engineering, model training, evaluation, deployment, and monitoring.
• Develop Retrieval-Augmented Generation (RAG) solutions and integrate LLMs into enterprise apps.
• Perform model evaluation, tuning, and prompt optimization.
• Develop scalable backend services and RESTful APIs using Python.
• Design data pipelines and integrate AI/ML models with internal/external systems via APIs.
• Design and deploy cloud-native solutions on AWS, Azure, or GCP.
• Build and maintain CI/CD pipelines for deployment and operations.

Skills

Python development

RESTful APIs

CI/CD

MLOps

Docker

Kubernetes

Cloud platforms

Data pipelines

AI/ML

Education

Bachelor's or Master's in CS/Engineering/Data Science

Tools

Docker

Kubernetes

SQL

Git

Airflow

Job description

Kforce Inc. in Coppell, TX seeks a Senior Python AI/ML Engineer to design, develop, test, and deploy enterprise AI/ML solutions with strong emphasis on Python and API engineering.

You will build end-to-end pipelines, implement MLOps practices, and integrate RAG and large language models into enterprise applications. The role covers data engineering, cloud-native deployments on AWS/Azure/GCP, and robust CI/CD using tools like Jenkins, GitHub Actions, Docker, and Kubernetes.