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

United States, Jersey, GeorgiaFull-time, ContractorPosted 9 days ago
Description

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

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