Applied Category Theory Research

Senior Manager, GTM Sales Engineer & AI solutions

Toast

Toast creates technology to help restaurants and local businesses succeed in a digital world, helping business owners operate, increase sales, engage customers, and keep employees happy. Retail is Toast's biggest bet and we are growing rapidly. The opportunity is massive, and the category is ours to define. You'll have the backing of Toast's scale, brand, and resources but you'll be on the team architecting how we operate, scale, and win.  The decisions you make in this role will shape how Toast competes in retail for years to come. Toast is prioritizing AI integration across the enterprise to redefine GTM velocity. As part of this strategy, multiple business units are pursuing specialized AI initiatives tailored to market challenges. This model balances corporate-wide coordination with vertical accountability: teams work in lockstep to scale efficiencies and aggregate impact, while remaining responsible for developing, building, and launching solutions optimized for unique operating environments. The GTM Sales Engineer & AI solutions is the core functional driver of this transformation within the Retail vertical. As an expert in applied AI, you will own the centralized deployment of AI applications to directly improve Productivity Per Rep (PPR). You will drive AI-powered productivity and automation across Retail sales, working with AEs and BDR/SDR teams to accelerate sales and with Onboarding to streamline the path to Customer Go-Live, with the opportunity to grow your impact across other GTM and client-facing teams as the vertical scales. You will be the operational linchpin running the Retail AI GTM Pod, architecting a continuous feedback loop sourcing grassroots ideas from the frontline, filtering them through a business lens, and scaling them into production tools. This is a technical, builder-focused role. You will observe decentralized AI applications working across the organization and partner to accelerate their impact, making them structurally better, integrating them into core systems, and maintaining them long-term. While you will partner with central corporate operations and marketing to advocate for Retail use cases and scale company-wide efficiencies, you will also possess the autonomous engineering capabilities to construct vertical-specific pipelines when distinct merchant workflows require it. This role sits in Revenue Operations, but will also dotted-line report into engineering. A day in the life (Responsibilities)  AI GTM POD GOVERNANCE & SOLUTION SOURCING * Leadership & Facilitation: Stand up the Retail AI GTM Pod to surface, qualify, and scale AI applications across the Retail field. The model could be a working group of AI-forward reps, managers, and leaders organized around defined themes in Sales & Onboarding, contributing domain expertise and frontline signals. The pod functions as an intake mechanism and sounding board, surfacing field experiments, pressure-testing priorities, and keeping your roadmap grounded in what moves the business. * Idea & Solution Sourcing: Serve as the production engine for ideas surfacing through the pod and field. Evaluate what is worth scaling, determine the right build, buy, or borrow path, and take the strongest ideas from experiment to production tool—launching with Enablement to non-technical end-users and maintaining active ownership through adoption tracking, feedback, and iteration. * Build vs. Buy Evaluation: Lead technical discovery to determine the most efficient path for problem statements, assessing whether to build a custom agentic solution, stitch existing APIs, or coordinate with vendors to purchase a scalable product. * Roadmap Prioritization: Translate decisions into a sprint-based roadmap, prioritizing developments based strictly on their potential to drive vertical PPR and eliminate administrative friction. APPLIED ENGINEERING & SYSTEMS INTEGRATION * Agile Sprint Execution: Maintain and execute against a technical scrum board, operating on defined sprint cycles to continuously ship, test, and iterate on AI-powered features. * Industrializing Frontline Wins: Take successful, unscaled local experiments (e.g., territory expansion scoring, contact discovery pipelines, multi-intent category parsers) and harden them with error handling, version control, scalable code, and secure coding practices like input validation, secrets management, and mitigation of LLM risks (e.g., prompt injection). * Systems Integration: Coordinate integration efforts to map vertical AI outputs into core GTM platforms (Salesforce, Snowflake, Taskray), ensuring local applications enhance rather than disrupt foundational enterprise pipelines. * Data Integrity Architecture: Build & monitor data validation frameworks ensuring model inputs are pristine and outputs are entirely auditable and trusted by the field. * Application Security: Design & enforce security controls for Retail AI applications, including authentication/authorization frameworks, secrets management, access controls on model outputs, and mitigations for LLM risks (prompt injection, data exfiltration). Ensure builds meet Toast's security standards given system proximity to payment and customer data workflows. CROSS-FUNCTIONAL PARTNERSHIP & STRATEGIC RADAR * Enterprise Collaboration: Contribute to cross-functional AI coordination cadences connecting Revenue Operations, Marketing AI, and Business Technology teams across Toast. Align on company-wide AI investments, advocate for Retail use cases and merchant requirements in shared roadmaps, and identify where central efforts can be leveraged, adapted, or extended. Serve as Retail's active voice in sequencing these shared initiatives while staying coordinated. * Vertical Personalization: Monitor central enterprise tool developments (e.g., prospecting or enablement agent suites) to identify opportunities to clone, customize, or extend for Retail merchant types. * Bidirectional Knowledge Exchange: Establish a pipeline for sharing locally developed code, architecture patterns, and prompt structures with central teams, ensuring Retail's breakthroughs help elevate Toast's engineering ecosystem. FLUENCY, ENABLEMENT & TRAINING LOOPS * AI Fluency Leadership: Design and execute vertical-wide enablement tracks to build a baseline of confident, independent AI tool usage across sales reps, onboarding consultants, and managers. * Adoption Analytics: Build & monitor adoption tracking mechanisms for deployed AI solutions, ensuring training translates into consistent field usage and measurable reductions in level of effort (LOE). What you'll need to thrive (Requirements) * Applied AI Deployment: 4+ years of experience in a technical, analytical, or GTM operations role, with a track record of owning the full deployment lifecycle of applied AI applications, RAG pipelines, or agentic workflows, including post-launch monitoring, alerting, rollback procedures, and model version management. * Modern AI Toolchain Literacy: Advanced, hands-on proficiency with developer-focused AI tools, specifically the Gemini Suite, Claude Cowork, and Claude Code. * Modern Deployment Stack: Experience deploying and operating AI backend systems in production (API services, model inference pipelines, orchestration layers), with demonstrated ownership through reliability, observability, and incident response. * Application Security Awareness: Familiarity with security best practices for AI-native systems, including authentication/authorization, secrets management, access controls on outputs, and awareness of LLM attack surfaces (prompt injection, data exfiltration). * Agile Operational Fluency: Experience operating within an agile engineering model, including managing technical product backlogs, running sprint cycles, and maintaining scrum boards. * Strategic Diplomacy: Exceptional communication skills with a proven ability to enter central enterprise forums, align stakeholders, advocate for vertical needs, and collaborate across business units. What will help you stand out (Nonessential Skills/Nice to Haves) * Software engineering or computer science background with the ability to write functional code (Python, JavaScript, or equivalent) and construct robust API integrations from scratch. * Direct domain familiarity with B2B SaaS and Retail tech spanning grocery, convenience, or wholesale commerce environments. * Experience building or scaling an AI program for non-technical end-users, including driving literacy, prompt engineering, or tool enablement. * Degree in Computer Science, Engineering, a related technical discipline, or equivalent practical experience as a technical founder or builder.   AI at Toast At Toast, one of our company values is that we're hungry to build and learn. We believe learning new AI tools empowers us to build for our customers faster, more independently, and with higher quality. We provide these tools across all disciplines, from Engineering and Product to Sales and Support, and are inspired by how our Toasters are already driving real value with them. The people who thrive here are those who embrace changes that let us build more for our customers; it’s a core part of our culture.   Our Total Rewards Philosophy  We strive to provide competitive compensation and benefits programs that help to attract, retain, and motivate the best and brightest people in our industry. Our total rewards package goes beyond great earnings potential and provides the means to a healthy lifestyle with the flexibility to meet Toasters’ changing needs. Learn more about our benefits at https://careers.toasttab.com/toast-benefits. The base salary range for this role is listed below. The starting salary will be determined based on skills, experience, and geographic location. In addition to base salary, our total rewards components include cash compensation (overtime, bonus/commissions if eligible), equity, and benefits. You can learn more about how we align pay with local labor markets in our Geographic Pay Zone Philosophy. Zone A $172,000—$275,000 USD Zone B $150,000—$240,000 USD Zone C $135,000—$216,000 USD How Toast Uses AI in its Hiring Process Throughout the hiring process, our goal is to get to know you. We use AI tools to support our recruiters and interviewers with tasks like note-taking, summarization, and documentation of interviews to ensure they can be fully focused on your conversation. All hiring decisions are made by people. To learn more: https://careers.toasttab.com/ai-in-hiring Our Approach to Hybrid Working We embrace a hybrid work model that fosters in-person collaboration while valuing individual needs. Our goal is to build a strong culture of connection as we work together to empower the hospitality community, regardless of location. Please visit the Locations page on our career site to learn more about our in-office expectations by region: https://careers.toasttab.com/locations-toast Diversity, Equity, and Inclusion is Baked into our Recipe for Success At Toast, our employees are our secret ingredient—when they thrive, we thrive. The restaurant industry is one of the most diverse, and we embrace that diversity with authenticity, inclusivity, respect, and humility. By embedding these principles into our culture and design, we create equitable opportunities for all and raise the bar in delivering exceptional experiences. We Thrive Together We embrace a hybrid work model that fosters in-person collaboration while valuing individual needs. Our goal is to build a strong culture of connection as we work together to empower the restaurant community. To learn more about how we work globally and regionally, check out: https://careers.toasttab.com/locations-toast. Apply today! Toast is committed to creating an accessible and inclusive hiring process. As part of this commitment, we strive to provide reasonable accommodations for persons with disabilities to enable them to access the hiring process. If you need an accommodation to access the job application or interview process, please contact candidateaccommodations@toasttab.com. ------ For roles in the United States, it is unlawful in Massachusetts to require or administer a lie detector test as a condition of employment or continued employment. An employer who violates this law shall be subject to criminal penalties and civil liability.

Applied Math Tutor

xAI

SpaceXAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. ABOUT THE ROLE: As an AI Tutor - Applied Math Specialist, you’ll play a key role in advancing SpaceXAI's mission by enhancing our AI technologies through high-quality inputs, labels, and annotations using specialized software. You’ll collaborate with our technical team to train models on human interactions, problem-solving, and discussions; refine annotation tools; and select/create challenging applied math problems to boost performance. All of our AI Tutor roles potentially involve gathering or providing data in text, voice, and video formats, including annotations, audio recordings, or video sessions—tasks with which candidates must be comfortable. RESPONSIBILITIES: * Use proprietary software applications to provide input/labels on defined projects. * Support and ensure the delivery of high-quality curated data. * Play a pivotal role in supporting and contributing to the training of new tasks, working closely with the technical staff to ensure the successful development and implementation of cutting-edge initiatives/technologies. * Interact with the technical staff to help improve the design of efficient annotation tools. * Choose problems from applied math domains that align with your expertise, focusing on areas such as probability, statistics, numerical analysis, optimization, operations research, dynamical systems, data modeling, and related fields where you can confidently provide detailed solutions and evaluate model responses. * Interpret, analyze, and execute tasks based on given instructions. BASIC QUALIFICATIONS: * Must have either (a) a Master’s or PhD in Mathematics with a specialization in a subdomain of applied mathematics (there is a separate position for pure math) or (b) a medal in an International Math Olympiad (IMO) or similar level math competition. * Proficiency in reading and writing, both in informal and professional English. * Strong ability to navigate various information resources and databases. * Outstanding communication, interpersonal, analytical, and organizational capabilities. * Solid reading comprehension skills combined with capacity to exercise autonomous judgment even when presented with limited data/material. * A strong passion for and commitment to technological advancements and innovation. PREFERRED SKILLS AND EXPERIENCE: * Math PhD with a specialization in a subdomain of applied mathematics. * Peer-reviewed applied math publications in well-regarded journals. * Previous AI Tutoring experience and/or experience teaching college courses. LOCATION AND OTHER EXPECTATIONS: * Tutor roles may be offered as full-time, part-time, or contractor positions, depending on role needs and candidate fit. * For contractor positions, hours will vary widely based on project scope and contractor availability, with no fixed commitments required.  On average most projects may involve at least 10 hours per week to achieve deliverables effectively though this is not a fixed commitment and depends on the scope of work. Contractors have full flexibility to set their own hours and determine the exact amount of time needed to complete deliverables.  * Tutor roles may be performed remotely from any location worldwide, subject to legal eligibility, time-zone compatibility, and role specific needs. * For US based candidates, please note we are unable to hire in the states of Wyoming and Illinois at this time. * We are unable to provide visa sponsorship. * For those who will be working from a personal device, your computer must be a Chromebook, Mac with MacOS 11.0 or later, or Windows 10 or later. COMPENSATION AND BENEFITS: US based candidates: $45/hour - $75/hour depending on factors including relevant experience, skills, education, geographic location, and qualifications. International candidates: Information will be provided to you during the recruitment process. Benefits vary based on employment type, location and jurisdiction. Benefits for eligible U.S. based positions include health insurance, 401(k) plan, and paid sick leave. Specific details and role specific information will be provided to you during the interview process. SpaceXAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.

Applied AI Engineer – OCR, Dokumentenklassifikation, Extraktion, RAG/LLM, Evaluation/QA (m/w/d) – Remote – Freelancer

MTR Legal

WIR sind MTR Legal Rechtsanwälte. Mittelständisch und international. Wir beraten im gesamten Familienrecht. Ein starker Wegbegleiter für nationale und internationale Mandanten. Wir verfolgen nicht nur Leistung, sondern schaffen auch Raum für Persönlichkeiten, um gemeinsam an einem Strang zu ziehen. Denn wir wissen: Mit Ihnen bringen wir unser Beratungsniveau für unsere Mandanten auf das nächste Level! DU Was du dafür können musst * LLM/RAG in Produktion (nicht nur Demo) * Dokumentenfokus (OCR/Extraktion/Klassifikation) oder sehr nah dran * Engineering: Versionierung, Repro, Tests, Monitoring * Evaluation-Mindset: Qualität messen & Regression verhindern Was am Ende stehen muss (Deliverables) * DocTypes + Extraktionsschemas (Top 10) inkl. Validierungen * OCR/Extraktionspipeline (Edge Cases: schlechte Scans, Tabellen, Stempel) * RAG/LLM: Summary + Mandanten-E-Mail-Draft + Action Items * Confidence/Checks: Thresholds, Rule/LLM-Checks, Human-in-the-loop Gates * QA/Eval: Golden Set, Metriken (Precision/Recall), Prompt/Model Regression Tests CONNECTING THE DOTS Tech (Orientierung) OCR/Extraction, LLM/RAG, Embeddings, Prompting/Templates, Eval Harness (Golden Sets), Monitoring/Drift. Integration in Workflow/Queue. Rahmenbedingungen * 100% Remote (CET/Europa ideal) * Projektbasis, Start asap, Auslastung nach Vereinbarung PERSPECTIVE Produktionsreife Document Intelligence: DocType → Felder → Summary → Draft → Checks. Wichtig: messbare Qualität, Regression-Schutz, sichere Gates (Human-in-the-loop).