AI/ML Lead

Programmers.io; Tampa (FL); On-site; USD 120,000 - 150,000; Full time

Job summary

Programmers.io is seeking an AI/ML Lead based in Tampa, FL, with responsibilities including overseeing AI initiatives and ensuring successful deployment of solutions. Ideal candidates will have strong skills in Python, FastAPI, and experience with Generative AI frameworks.

This full-time position requires 10+ years of professional experience in software development, emphasizing system architecture and cloud deployments. The role supports a dynamic work environment that values innovation and problem-solving.

Qualifications

• 10+ years of professional experience in software development and system design.
• Hands-on experience with AI/ML frameworks and deployment.

Skills

Python expertise

FastAPI for API development

Generative AI frameworks

RAG architecture

Cloud platforms (AWS, Azure, GCP)

Vector databases

Problem-solving skills

Tools

Docker

Kubernetes

Job description

One of our clients operating globally is looking for an AI/ML Lead located in Tampa, FL, or Dallas, TX (3 days onsite).

Location: Tampa, FL, Dallas TX (3 days onsite)

Duration: Full time with all benefits

Experience: 10+ years of professional experience in software development and system design.

Required Skills:

• Strong proficiency in Python and experience with FastAPI for API development.
• Hands‑on experience with Generative AI frameworks and Retrieval-Augmented Generation (RAG) architectures.
• Solid understanding of system and architecture design principles for distributed applications.
• Experience deploying solutions on any major cloud platform (AWS, Azure, GCP).
• Familiarity with vector databases, embedding models, and retrieval pipelines.
• Strong problem‑solving skills and ability to work in a fast‑paced environment.

Preferred Qualifications:

• Experience with LLM fine‑tuning, prompt engineering, and model evaluation.
• Knowledge of containerization (Docker) and orchestration (Kubernetes).
• Exposure to CI/CD pipelines and DevOps practices.