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Job Title: AI/ML Engineer
Fully remote within the United States
Role Type: Contract engagement
Production AI/ML engineering experience with advanced Python skills and strong machine learning fundamentals
Hands-on experience with Generative AI, LLMs, RAG, embeddings, and vector databases
Experience deploying AI/ML solutions on AWS, Azure, or GCP
MLOps/LLMOps experience, including APIs, model evaluation, monitoring, and production deployment
Experience with LangChain, LlamaIndex, or similar AI application frameworks
Experience with prompt engineering, fine-tuning, and AI application development
Design, develop, test, and deploy production-ready AI/ML models and applications
Build Generative AI and LLM-powered solutions, including RAG pipelines, embeddings, vector search, and prompt-based applications
Develop scalable APIs, microservices, backend integrations, and data pipelines supporting model training, evaluation, and inference
Improve model and application accuracy, performance, reliability, and scalability
Implement MLOps/LLMOps practices for deployment, monitoring, versioning, evaluation, and model lifecycle management
Collaborate across engineering, data, product, and business teams to translate requirements into production AI solutions
Research and evaluate emerging AI technologies, frameworks, models, and development approaches
Preferred experience with enterprise-scale production AI deployments and platforms such as Azure OpenAI, AWS Bedrock, Vertex AI, OpenAI APIs, or Anthropic Claude
Preferred experience with AI agents, agentic workflows, tool calling, and vector databases such as Pinecone, Weaviate, Milvus, or FAISS
Familiarity with AI security, responsible AI, model governance, and data privacy is preferred
Job Title: AI/ML Engineer
Fully remote within the United States
Role Type: Contract engagement
Production AI/ML engineering experience with advanced Python skills and strong machine learning fundamentals
Hands-on experience with Generative AI, LLMs, RAG, embeddings, and vector databases
Experience deploying AI/ML solutions on AWS, Azure, or GCP
MLOps/LLMOps experience, including APIs, model evaluation, monitoring, and production deployment
Experience with LangChain, LlamaIndex, or similar AI application frameworks
Experience with prompt engineering, fine-tuning, and AI application development
Design, develop, test, and deploy production-ready AI/ML models and applications
Build Generative AI and LLM-powered solutions, including RAG pipelines, embeddings, vector search, and prompt-based applications
Develop scalable APIs, microservices, backend integrations, and data pipelines supporting model training, evaluation, and inference
Improve model and application accuracy, performance, reliability, and scalability
Implement MLOps/LLMOps practices for deployment, monitoring, versioning, evaluation, and model lifecycle management
Collaborate across engineering, data, product, and business teams to translate requirements into production AI solutions
Research and evaluate emerging AI technologies, frameworks, models, and development approaches
Preferred experience with enterprise-scale production AI deployments and platforms such as Azure OpenAI, AWS Bedrock, Vertex AI, OpenAI APIs, or Anthropic Claude
Preferred experience with AI agents, agentic workflows, tool calling, and vector databases such as Pinecone, Weaviate, Milvus, or FAISS
Familiarity with AI security, responsible AI, model governance, and data privacy is preferred
Machine Learning Engineer (United States) in remote at Unknown Company
This position is listed as contract and able to be worked remotely.