Software Engineer, macOS Core Product - Montreal, Canada
Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for diverse use cases; deploy and operate core ML 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.
Software Engineer, macOS Core Product - Vancouver, Canada
Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for a diverse range of use cases. Deploy and operate the core ML inference workloads for the AI Voices serving pipeline. Introduce new techniques, tools, and architecture to improve the performance, latency, throughput, and efficiency of deployed models. Build tools to provide visibility into bottlenecks and sources of instability and design and implement solutions to address the highest priority issues.
Software Engineer, macOS Core Product - Calgary, Canada
Work alongside machine learning researchers, engineers, and product managers to bring AI Voices to customers for diverse use cases. Deploy and operate the core ML 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.
Freelance AI Trainer - Civil Engineering & Python
The role involves designing technically rigorous civil engineering problems grounded in practice, evaluating AI solutions for engineering accuracy and assumptions, using Python (NumPy, Pandas, SciPy) to validate calculations or analyze outputs, improving AI reasoning to align with codes, standards, and professional logic, and applying structured scoring criteria to assess model performance.
Mechanical Engineer with Python Experience - Freelance AI Trainer
Train and evaluate AI models on complex, real-world mechanical engineering problems. 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.
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.
Forward Deployed Engineer
Design, build, and deploy predictive AI features, including natural language detection, autosuggestions, and intelligent prompt recommendations. Leverage Warp’s extensive user-generated content and team data to continuously refine AI prediction and personalization. Drive substantial improvements in code generation quality, including code completions, diff applications, and SWEbench performance. Implement and iterate specialized agents tailored for specific developer workflows and use cases. Optimize AI models through fine-tuning, advanced prompt engineering, and robust, data-driven feedback loops. Improve context retrieval systems, enabling Warp agents to retain and utilize memory effectively. Collaborate closely with product and engineering teams, rapidly shipping iterative improvements into production. Continuously elevate the user experience by refining interactions between developers and Warp AI.
Freelance AI Evaluation Scenario Writer
The role involves designing realistic and structured evaluation scenarios for LLM-based agents, creating test cases that simulate human-performed tasks and defining gold-standard behavior to compare agent actions against. Responsibilities include creating structured test cases that simulate complex human workflows, defining gold-standard behavior and scoring logic to evaluate agent actions, analyzing agent logs, failure modes, and decision paths, working with code repositories and test frameworks to validate scenarios, iterating on prompts, instructions, and test cases to improve clarity and difficulty, and ensuring that scenarios are production-ready, easy to run, and reusable.
MCP & Tools Python Developer - Agent Evaluation Infrastructure
Develop and maintain MCP-compatible evaluation servers, implement logic to check agent actions against scenario definitions, create or extend tools used by writers and QAs to test agents, work closely with infrastructure engineers to ensure compatibility, and occasionally assist with test writing or debugging sessions.
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