AI/ML Engineer
Role details
Job location
Tech stack
Job description
Our client is a pioneering company building advanced Machine Learning and Generative AI solutions that deliver real business value. Based in Los Angeles, this is a full-time and fully-onsite hands-on AI/ML Engineer contract role. You'll use state-of-the-art technologies-including Python, LLMs, Vector Databases, and Azure OpenAI-to design, build, and deploy production-grade systems for diverse enterprise needs. This is a role for engineers who want to innovate at every stage of the ML lifecycle. You'll create impact by owning full-cycle ML and GenAI applications: from prompt engineering and document processing to embedding-based search and cloud-deployed pipelines. The team values creative problem-solving, technical depth, and cross-functional collaboration-making this an excellent environment for rapid growth, learning, and career advancement. Contract duration: 6 months with possible extension, 40% Python, Machine Learning, Model Training 25% LLM, Prompt Engineering, and GenAI Workflows 20% Vector Database & MongoDB Integration 15% Cloud Deployment (Azure), CI/CD, MLOps Daily Responsibilities 70% Hands-On ML/GenAI Engineering 20% Team Collaboration & Feature Delivery 10% Technical Planning & Guidance The Offer 6+ months contract You will receive the following benefits: Medical, Dental, and Vision Insurance ??????? Applicants must be currently authorized to work in the US on a full-time basis now and in the future.
Requirements
Expert-level Python experience Machine Learning & Model Training Experience with tagging and labeling workflows Generative AI & LLMs (including prompt engineering) Document extraction, parsing, and chunking Handling structured & unstructured data Embedding generation and vector search Vector Database integration MongoDB Production-ready, scalable ML engineering Desired Skills & Experience Experience with Azure OpenAI APIs CI/CD best practices, cloud deployment (Azure preferred) Observability, monitoring, and evaluation frameworks Retrieval-Augmented Generation (RAG) pipelines Agentic AI workflow development Strong cross-functional teamwork and communication