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