AI Developer

Job Title: AI Developer

Location: Austin, TX

Job Type: Only W2

Job Description:

·       Design, develop, and maintain AI-powered applications and services.

·       Build and optimize machine learning models for business use cases.

·       Develop applications using Large Language Models (LLMs) such as GPT, Claude, Gemini, or open-source models.

·       Implement Retrieval-Augmented Generation (RAG) pipelines using vector databases.

·       Integrate AI models with web applications and enterprise systems using APIs.

·       Fine-tune, evaluate, and monitor AI models for performance and accuracy.

·       Collaborate with product managers, data scientists, and software engineers to deliver AI solutions.

·       Ensure AI applications follow security, privacy, and ethical AI best practices.

·       Stay current with advancements in AI, machine learning, and generative AI technologies.

Required Qualifications:

·       Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.

·       1–3 years of experience in AI/ML development.

·       Strong programming skills in Python.

·       Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn.

·       Hands-on experience with LLMs and prompt engineering.

·       Experience with RAG architectures and vector databases (e.g., Pinecone, Chroma, FAISS, or Milvus).

·       Knowledge of REST APIs, microservices, and cloud platforms (AWS, Azure, or Google Cloud).

·       Familiarity with SQL and NoSQL databases.

·       Experience using Git and CI/CD pipelines.

·       Preferred Skills

·       Experience with AI orchestration frameworks such as LangChain or LlamaIndex.

·       Knowledge of AI agents and workflow automation.

·       Experience deploying AI models using Docker and Kubernetes.

·       Understanding of MLOps concepts and model lifecycle management.

·       Familiarity with data engineering tools and ETL pipelines.

Technical Skills:

·       Python

·       Machine Learning

·       Deep Learning

·       Generative AI

·       Large Language Models (LLMs)

·       Prompt Engineering

·       RAG

·       Vector Databases

·       FastAPI or Flask

·       REST APIs

·       Git

·       Docker

·       Kubernetes

·       Cloud Platforms (AWS, Azure, or Google Cloud)