Statistics & Python Expert - Freelance AI Trainer
Contributors may design original computational statistics problems that simulate real mathematical research workflows, create problems requiring Python programming to solve using libraries such as Numpy, SciPy, and Sympy, ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes, develop problems requiring non-trivial reasoning chains in areas like number theory, combinatorics, graph theory, and numerical analysis, base problems on real research challenges or practical applications from mathematical practice, verify solutions using Python with standard mathematical libraries, and document problem statements clearly while providing verified correct answers.
AI/ML Engineer
Develop, train, and optimize machine learning models for various mobile app features. Research and implement state-of-the-art AI techniques to improve user engagement and app performance. Collaborate with cross-functional teams to integrate AI-driven solutions into applications. Design and maintain scalable ML pipelines, ensuring efficient model deployment and monitoring. Analyze large datasets to derive insights and drive data-driven decision-making. Stay updated with the latest AI trends and best practices, incorporating them into development processes. Optimize AI models for mobile environments to ensure high performance and low latency.
AI Product Manager
As an AI Product Manager, you will define and drive the AI product roadmap ensuring alignment with business objectives and user needs. You will collaborate with cross-functional teams including engineering, design, and marketing to develop and launch AI-powered features. Responsibilities include conducting market research and analyzing user feedback to identify opportunities for AI integration, working closely with data scientists and machine learning engineers to optimize AI models for accuracy, performance, and user impact, defining key performance indicators to measure success and iterating based on data-driven insights, staying up to date with AI trends, emerging technologies, and best practices, and ensuring ethical AI usage and compliance with data privacy regulations. This role is fully onsite in Lisbon, involving close in-person collaboration in a dynamic and fast-paced environment.
Parcel Contract Intelligence Consultant
Ship critical infrastructure by managing real-world logistics and financial data for the largest enterprise in the world. Own the why by building deep context through customer calls and understanding Loop’s value to customers, pushing back on requirements if a better, faster solution exists. Work across system boundaries with full-stack proficiency, including frontend UX, LLM agents, database schema, and event infrastructures. Leverage AI tools to automate boilerplate work, focusing on quality, architecture, and product taste. Constantly optimize development loops, refactor legacy patterns, automate workflows, and fix broken processes to raise the velocity bar.
Manager, Forward Deployed Engineering - Munich
Lead and grow a team of Forward Deployed Engineers (FDE) delivering production systems with frontier models. Own end-to-end delivery outcomes through clarity, speed, tight coordination, and technical quality. Codify effective practices into tools, playbooks, and roadmap inputs to create leverage for OpenAI and the wider developer community. Identify and raise early indicators with urgency from product behavior, customer environments, or delivery practices. Use judgment to decide when action is required. Set high performance standards for FDEs and support each individual's growth through direct, actionable feedback. Define staffing and support strategies for scalable field teams without added complexity.
Requirements Engineer - Physical Products
The candidate will be responsible for defining operational domains and evaluating the reliability of AI capabilities developed in-house. They will develop and extend state-of-the-art methods in uncertainty quantification and uncertainty calibration. This role involves understanding the AI systems built by the company, interfacing with them, and assessing their robustness in both real-world and adversarial scenarios. The candidate will contribute to impactful projects and collaborate with team members across different teams and backgrounds.
Systems Engineer - Physical Products
You will be responsible for defining operational domains and evaluating the reliability of the AI capabilities developed in-house. You will develop and extend the state-of-the-art in uncertainty quantification and uncertainty calibration. This will involve understanding the AI systems built, interfacing with them, and evaluating their robustness in real-world and adversarial scenarios. You will contribute to impactful projects and collaborate with people across several teams and backgrounds.
Mathematics & Python Expert - Freelance AI Trainer
Contributors design original computational mathematics problems that simulate real mathematical research workflows; create problems requiring Python programming to solve using libraries like Numpy, SciPy, and Sympy; ensure problems are computationally intensive and not solvable manually within reasonable timeframes; develop problems requiring non-trivial reasoning chains in areas such as number theory, combinatorics, graph theory, and numerical analysis; base problems on real research challenges or practical applications; verify solutions using Python with standard mathematical libraries; and document problem statements clearly with verified correct answers.
Mathematics & Python Expert - Freelance AI Trainer
Contributors may design original computational mathematics problems that simulate real mathematical research workflows, create problems requiring Python programming to solve (using Numpy, SciPy, Sympy), ensure problems are computationally intensive and cannot be solved manually within reasonable timeframes (days/weeks), develop problems requiring non-trivial reasoning chains in areas like number theory, combinatorics, graph theory, and numerical analysis, base problems on real research challenges or practical applications from mathematical practice, verify solutions using Python with standard mathematical libraries, and document problem statements clearly while providing verified correct answers.
Material Data Specialist
You will be responsible for defining operational domains and evaluating the reliability of the AI capabilities developed in-house. You will develop and extend state-of-the-art methods in uncertainty quantification and uncertainty calibration. This will involve understanding the AI systems built, interfacing with them, and evaluating their robustness in real-world and adversarial scenarios. You will contribute to impactful projects and collaborate with people across several teams and backgrounds.
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