Point your AI agent at freehire and let it find you a job. A CLI and an MCP server over the whole job API — no browser.
Senior AI Engineer builds and deploys production-grade ML and LLM systems, turning business needs into scalable AI pipelines and models using Python and SQL.
Build and deploy LLM-powered agentic systems that autonomously perform structured tasks, integrating AI into existing software with a focus on reliability and scalability.
Build and deploy production-grade AI systems using RAG, agentic frameworks (LangGraph, AutoGen), and vector search (Azure AI Search, pgvector) with Python and cloud tools.
Build and optimize ML models, LLMs, and RAG systems using Python, TensorFlow, and PyTorch, and deploy them on cloud platforms like AWS or Azure.
Design and build autonomous AI agents that decompose goals into actionable steps, integrate with enterprise systems, and deploy robust, observable agentic workflows with built-in failure handling.
Build autonomous AI agents and data pipelines using LangChain/LangGraph or Google Vertex AI Agent Builder to automate analytics and decision-making at scale.
Senior AI Engineer designs and deploys enterprise AI systems using TensorFlow, PyTorch, and LLM APIs, building scalable ML pipelines and computer vision/NLP solutions for fintech and healthcare clients.
Build full-stack AI applications using .NET, C#, React/Next.js, and Node.js, integrating LLMs with RAG, vector search, and tool-calling for scalable business automations.
Lead the backend and data engineering behind a next-gen RAG system, building scalable Apache Beam pipelines, Google Cloud Spanner graph queries, and FastAPI/Temporal services to power deterministic LLM agents.
Build and deploy production-grade ML models and data pipelines, collaborating with engineers to support IoT, robotics, and GenAI use cases on a large-scale data platform.
Lead data analytics and AI initiatives at a global renewable energy firm, building ML models, LLMs, and automation to drive climate-focused business decisions using Python, SQL, and cloud platforms.
Build production-grade AI systems for clinical research using RAG, agentic workflows, and large-scale data pipelines across EHRs and PDFs.
Principal ML Engineer builds and deploys GenAI features for business planning, integrating LLMs, prompt engineering, RAG, and agentic workflows into production systems using Python, MLOps, and cloud-native infra.
Principal AI Engineer builds and deploys AI systems for an education-tech suite, integrating LLMs, RAG, and agentic frameworks to power admissions assistants and internal tools while leading AI adoption across teams.
Build and deploy enterprise-grade retrieval and knowledge systems for Scale GP, including RAG pipelines, vector stores, and context engines that power AI agents for customers.
Senior AI Engineer builds and deploys agentic LLM systems using frameworks like LangGraph and Crew AI to power Profitero+'s ecommerce analytics and automation tools.
Build and deploy large language models to automate real-world processes in healthcare, government, and energy sectors, turning research into production-grade AI solutions.
Build and deploy production-grade AI models (LLMs, agents, RAG) to automate workflows in healthcare, government, and energy sectors.
Build and integrate AI agents to automate performance and UI testing workflows using Python, LLMs, and tools like Selenium and JMeter.
Builds and maintains cloud-based data pipelines and SQL models on GCP, using BigQuery, dbt, and Airflow to support data-driven business processes in an international agile team.
We couldn't check your fit for this role — add a CV to your profile to see it next time.
