Software Engineer, macOS Core Product - Seoul, South Korea
Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for a variety of use cases; deploy and operate core machine learning inference workloads for the AI Voices serving pipeline; introduce new techniques, tools, and architecture to improve performance, latency, throughput, and efficiency of deployed models; build tools to identify bottlenecks and sources of instability and design and implement solutions to address the highest priority issues.
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.
Member of Technical Staff - ML Research Engineer; Multi-Modal - Audio
Invent and prototype new model architectures that optimize inference speed, including on edge devices; build and maintain evaluation suites for multimodal performance across a range of public and internal tasks; collaborate with the data and infrastructure teams to build scalable pipelines for ingesting and preprocessing large audio datasets; work with the infrastructure team to optimize model training across large-scale GPU clusters; contribute to publications, internal research documents, and thought leadership within the team and the broader ML community; collaborate with the applied research and business teams on client-specific use cases.
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.
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.
Access all 4,256 remote & onsite AI jobs.
Frequently Asked Questions
Need help with something? Here are our most frequently asked questions.
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Suspendisse varius enim in eros elementum tristique. Duis cursus, mi quis viverra ornare, eros dolor interdum nulla, ut commodo diam libero vitae erat. Aenean faucibus nibh et justo cursus id rutrum lorem imperdiet. Nunc ut sem vitae risus tristique posuere.