GenAI / Machine Learning / Python Engineer - USC / Green Card / H4 EAD

About the Opportunity

We are looking for a skilled GenAI / Machine Learning / Python Engineer with 2–6 years of professional experience to join a growing technology team. The ideal candidate will have strong Python and Machine Learning fundamentals, along with hands-on experience building AI/ML solutions and an interest in Generative AI and emerging AI technologies.

This opportunity is well suited for professionals who have worked on real-world AI/ML projects and are looking to contribute to production-focused solutions involving Machine Learning, Generative AI, LLMs, and data-driven applications.

Employment Type: Full-Time W2

• Experience: 2–6 Years
• Work Authorization: USC / Green Card / H4 EAD
• Location: Open to Relocation Anywhere in the United States
• Employment: W2 Only — No C2C / 1099

Key Responsibilities

• Develop, test, and maintain Machine Learning and AI solutions using Python.
• Build and integrate Generative AI and LLM-based applications.
• Work with structured and unstructured data to identify patterns and generate insights.
• Develop and optimize ML models for real-world business applications.
• Implement data preprocessing, feature engineering, model training, evaluation, and optimization.
• Work with LLM APIs, prompt engineering, embeddings, and AI/ML frameworks.
• Develop or support Retrieval-Augmented Generation (RAG) solutions where applicable.
• Collaborate with engineering, data, and business teams to understand requirements and deliver AI-driven solutions.
• Deploy and monitor AI/ML applications in development or production environments.
• Document technical solutions, methodologies, and model performance.

GenAI Skills – Preferred

Candidates with hands-on experience in the following areas are highly preferred

• Generative AI and Large Language Models (LLMs)
• Prompt Engineering
• Retrieval-Augmented Generation ( RAG )
• Vector databases such as Pinecone, FAISS, Chroma, Weaviate, or similar
• LangChain, LlamaIndex, or comparable GenAI frameworks
• LLM APIs such as OpenAI, Azure OpenAI, Gemini, Claude, Llama, or similar
• Embeddings and semantic search
• NLP and Transformer architectures
• Fine-tuning or model customization
• AI agents / Agentic AI

Cloud & Deployment – Nice to Have

• Experience with AWS, Azure, or GCP
• Docker and containerization
• REST APIs and microservices
• CI/CD
• Kubernetes
• ML deployment and monitoring / MLOps