Software Engineer, Evaluation Frontend
As an Evaluation Frontend Software Engineer, you will design tools and visualizations that enable researchers and engineers to compare and analyse hundreds of model evaluations, including both data visualization tools and statistical tools to extract signal from noisy data. You will develop an understanding of the relative merits and limitations of each model evaluation and suggest new facets of model evaluation. Your work will involve collaborating closely with cross-functional teams, including researchers and engineers, to surface necessary insights for model development.
Data Scientist - Manufacturing Data (KR)
Design and implement customized AI solutions for manufacturing; analyze manufacturing data to uncover opportunities and develop AI models; collaborate with customers to understand their requirements and deliver clear, data-driven solutions; work closely with internal teams to ensure solutions are feasible, scalable, and aligned with product strategy; present findings to both technical and non-technical stakeholders.
Freelance Cybersecurity Analyst - AI Trainer
Analyze and investigate simulated security alerts and incidents across endpoints, identities, and cloud environments. Conduct proactive threat hunting using KQL or similar query languages to identify hidden vulnerabilities and emerging threats that automated systems may miss. Assess the accuracy and depth of AI-generated security incident reports and threat analyses. Review, validate, and improve the model’s understanding of Microsoft Defender products and SOC workflows. Provide expert feedback on AI performance in identifying and classifying cybersecurity threats.
Finance Platform Engineer
Use proprietary software applications to provide input and labels on defined projects. Support and ensure the delivery of high-quality curated data. Contribute to the training of new tasks by working closely with the technical staff to develop and implement cutting-edge initiatives and technologies. Interact with technical staff to improve the design of efficient annotation tools. Choose problems from economics fields that align with expertise, focusing on macroeconomics, microeconomics, and behavioral economics. Regularly interpret, analyze, and execute tasks based on given instructions. Provide services including labeling and annotating data in text, voice, and video formats to support AI model training, sometimes involving recording audio or video sessions.
[UMOS ONE] Data & AI Engineering Lead
The responsibilities include developing AI models and integrating Agentic AI for routing, dispatching, and prediction, specifically using features extracted from knowledge graphs to develop AI-based optimal routing, dispatching technologies, demand prediction, ETA prediction, and improving analytic prediction models. The role also involves designing and implementing the integration architecture with Agentic AI systems. Additionally, responsibilities cover the design and development of mobility and logistics-specific ontologies, building knowledge graph-based data models, integrating and refining large heterogeneous data, and managing relationships among service entities to enhance data intelligence. Furthermore, the position requires designing, building, and operating large-scale data pipelines (ETL/ELT) for UMOS platforms, establishing and automating MLOps pipelines for stable model operation, and developing and integrating efficient API interfaces with service backend systems.
[UMOS ONE] Data Analytics Engineer
Design and develop the Agentic AI system including the core architecture and modules of UMOS platform's autonomous decision-making system. Develop agent systems integrating AI-based routing, dispatching, and predictive models into actual service operation logic. Implement software logic that reacts in real-time to dynamic changes in mobility and logistics operations to make optimal decisions. Enhance agent decision-making ability using knowledge graph-based information. Design and operate distributed systems to ensure the stability and scalability of the agent system. Build simulation and test environments to verify the complex logic and decision-making processes of the Agentic AI system. Develop tools to monitor and analyze the performance, behavior, and safety of the operating agent system.
Data Engineer – Spark Specialist
Help users discover and master the Dataiku platform through user training, office hours, demos, and ongoing consultative support. Analyse and investigate various kinds of data and machine learning applications across industries and use cases. Provide strategic input to the customer and account teams that help make customers successful. Scope and co-develop production-level data science projects with customers. Mentor and help educate data scientists and other customer team members to aid in career development and growth.
[UMOS ONE] Backend Engineer (Capora 물류시스템)
Design and develop scalable backend services operating in cloud environments; develop backend and algorithm features for AI-based functionalities such as price prediction, route optimization, and automation services; develop stable B2B API integration with external partners and corporate clients; analyze functional requirements and design API interface structures; continuously refactor for service performance monitoring and structural improvement; participate in code reviews and technical decision-making to enhance quality; ensure stability and high availability of services operated in cloud and container-based environments.
Product Marketing Manager, Developer Platform
As Product Marketing Manager, you drive go-to-market strategies for OpenAI’s developer platform, focusing on adoption, strategic launch planning, and growth of APIs among developers and businesses. You collaborate closely with Product, Engineering, and GTM teams to develop product positioning, messaging, marketing plans, post-launch campaigns, and customer/market insights.
Software Engineer, Monetization Infrastructure
You will design and build backend and infrastructure systems for OpenAI’s monetization and ads stack, emphasizing reliability, privacy, security, and large-scale performance. You’ll develop APIs and platforms, drive 0→1 infrastructure projects, and collaborate cross-functionally with Product, Research, and Design teams.
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