Freelance AI Trainer - Civil Engineering & Python
Design technically rigorous civil engineering problems grounded in practice. Evaluate AI solutions for engineering accuracy and assumptions. Use Python (NumPy, Pandas, SciPy) to validate calculations or analyze outputs. Improve AI reasoning to align with codes, standards, and professional logic. Apply structured scoring criteria to assess model performance.
Electrical Engineer with Python Experience - Freelance AI Trainer
The role involves designing rigorous electrical engineering problems that reflect professional practice, evaluating AI solutions for correctness, assumptions, and constraints, validating calculations or simulations using Python (including libraries such as NumPy, Pandas, and SciPy), improving AI reasoning to align with industry-standard logic, and applying structured scoring criteria to multi-step problems.
Mechanical Engineer with Python Experience - Freelance AI Trainer
Design graduate- and industry-level mechanical engineering problems grounded in real practice. Evaluate AI-generated solutions for correctness, assumptions, and engineering logic. Validate analytical or numerical results using Python (NumPy, SciPy, Pandas). Improve AI reasoning to align with first principles and accepted engineering standards. Apply structured scoring criteria to assess multi-step problem solving.
Staff AI Engineer
Design and implement AI agents and extend existing agents with new capabilities including managing agent context using techniques like sub-agents and retrieval-based context management. Develop complex tools for agents such as computer use and browser use. Research and develop multi-agent orchestration and tool calling systems to enable collaboration between agents. Build and maintain production-grade APIs and AI-powered features across backend services and user-facing experiences. Evaluate AI performance through tests and evaluations and iterate on prompts, agent tools, and orchestration to improve output quality and reliability.
Senior AI Engineer
Develop AI agents and multi-agent systems by designing and implementing agents and extending existing agent capabilities, including managing the agent's context using techniques like sub-agents and retrieval-based context management. Develop complex tools for agents such as computer use and browser use. Research and build systems for multi-agent orchestration and agent tool calling to manage collaboration and tool usage. Engage in full-stack development to build and maintain production-grade APIs and AI-powered features, covering backend services to user-facing experiences. Evaluate AI performance using tests and evaluations to iterate and improve prompts, agent tools, and orchestration for better output quality and reliability.
Enterprise Account Executive - Italy
The AI Outcomes Manager will partner with executive sponsors and end users to identify high-impact use cases and turn them into measurable business outcomes on Glean. They will lead strategic reviews and advise customers on their AI roadmap to ensure maximum value from Glean's platform. The role involves translating business needs into clear problem statements, success metrics, and practical AI solutions while collaborating with Product and R&D to shape priorities. They will conduct discovery workshops, scope pilots, and guide rollouts to drive broad and deep adoption of the Glean platform. Additionally, they will design and build AI agents with and for customers, including rethinking and redesigning underlying business processes to maximize impact and usability. The manager will proactively identify expansion opportunities and drive engagement across teams and functions.
Senior AI Engineer - San Mateo, CA
The role involves training, evaluating, and monitoring new and improved LLMs and other algorithmic models. The engineer will test and deploy content moderation models in production and iterate based on real-world performance metrics and feedback loops. They are expected to develop medium to long-term vision for content understanding-related R&D, collaborating with management, product, policy & operations, and engineering teams. The position requires taking ownership of results delivered to customers, advocating for changes in approach where needed, and leading cross-functional execution.
MCP & Tools Python Developer - Agent Evaluation Infrastructure
Developing and maintaining MCP-compatible evaluation servers, implementing logic to check agent actions against scenario definitions, creating or extending tools that writers and QAs use to test agents, working closely with infrastructure engineers to ensure compatibility, and occasionally helping with test writing or debug sessions when needed.
Evaluation Scenario Writer - AI Agent Testing Specialist
Design realistic and structured evaluation scenarios for LLM-based agents by creating test cases that simulate human-performed tasks and defining gold-standard behavior to compare agent actions against. Create structured test cases that simulate complex human workflows. Define gold-standard behavior and scoring logic to evaluate agent actions. Analyze agent logs, failure modes, and decision paths. Work with code repositories and test frameworks to validate scenarios. Iterate on prompts, instructions, and test cases to improve clarity and difficulty. Ensure scenarios are production-ready, easy to run, and reusable.
Staff Backend Solution Architect Engineer
Architect and build backend services that power LLM-based agents and clinical automations. Design robust APIs and data models that are secure, observable, and extensible for other teams. Optimize performance and cost by profiling hot paths, tuning databases, and right-sizing cloud resources. Automate quality by writing unit and integration tests, crafting alerts, and owning on-call runbooks to ensure trust in every interaction. Partner with product, AI, and front-end engineers to ship new capabilities from concept to production within weeks.
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