AI Engineer - 100% Remote

Direct candidates only – NO THIRD PARTIES PLEASE. Resource 1 is seeking an AI Engineer for a remote contract with our client in the United States. The initial contract is for 6 months with strong likelihood of extensions. Due to the long-term need, position is also open for conversion to perm. Individual will join a team responsible for the development and integration of next-generation AI solutions. Individual will work closely with Product Leaders, Researchers, and Engineers to design, develop, and deploy AI-driven systems. This role is ideal for someone who thrives in a fast-paced, R&D-oriented environment and is passionate about delivering scalable, intelligent solutions using the latest advancements in AI. RESPONSIBILITIES: • Design and implement AI/ML models and pipelines using state-of-the-art tools and frameworks (e.g., PyTorch, TensorFlow, JAX). • Optimize LLMs, vision models, or multimodal systems (using Hugging Face, LangChain, OpenAI API, etc.). • Build, test, and deploy AI apps and APIs in prod environments (AWS, GCP, Azure, or similar). • Integrate AI services (OpenAI, Anthropic, Cohere, or open-source models like Mistral, LLaMA). • Collaborate with stakeholders to translate business needs into scalable AI solutions. • Stay current with the latest research, publications, and tools in the AI ecosystem. • Contribute to documentation, model evaluations, and ethical/secure deployment practices. TECH STACK & TOOLS: • Languages: Python (preferred), JavaScript/ TypeScript (for APIs or tooling) • Frameworks/ Libraries: PyTorch, TensorFlow, Hugging Face Transformers, LangChain, Ray • Cloud & MLOps: AWS (SageMaker, Lambda), Docker, Kubernetes, MLflow • AI/LLM Providers: OpenAI, Anthropic, Cohere, Google Vertex AI, Meta, Mistral • Databases: PostgreSQL, Redis, Pinecone, Weaviate (or similar vector DBs) • Version Control & CI/CD: GitHub, GitLab, CircleCI QUALIFICATIONS: Must-Have: • Strong experience in AI/ML engineering or applied data science • Experience developing and deploying ML models in production • Experience with LLMs (e.g., GPT-4, Claude, Mistral) or foundation models • Familiarity with prompt engineering, RAG, fine-tuning, or distillation techniques • Python programming skills and software engineering practices • RESTful API design and integration of AI services Nice-to-Have: • Experience in MLOps or model monitoring in production environments • Contributions to open-source AI/ML projects or publications • Familiarity with data privacy and model governance best practices • Experience building AI-powered agents or automation pipelines