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SUMMARY OF THE ROLE: As ML Engineer at Maze, you'll be the technical leader driving our machine learning infrastructure from experimentation to production, ensuring our AI-powered cybersecurity solutions deliver measurable impact for customers worldwide. This is a unique opportunity to join as one of the early engineering team members of a well-funded startup building breakthrough applications of LLMs and AI agents in cybersecurity. You'll take full ownership of evaluation frameworks, production ML pipelines, and cross-team ML integration, working closely with our CTO and product teams to transform cutting-edge AI research into robust, scalable solutions that solve real security challenges. Your success will be measured by agent performance improvements and product innovation impact, not just technical metrics. This role is perfect for a hands-on ML engineer who has scaled production ML systems across multiple companies, thinks like a product builder, and wants to drive the actual productionization of LLMs and ML to solve significant pain points. YOUR CONTRIBUTIONS TO OUR JOURNEY: * Build Production-Grade Evaluation Systems: Design and implement comprehensive evaluation frameworks that measure agent performance, track improvements over time, and ensure our AI systems deliver consistent value to customers * Drive Experimentation-to-Production Pipeline: Own the entire ML lifecycle from prototype to production, building scalable systems that enable rapid iteration while maintaining reliability and performance in customer environments * Enable Cross-Team ML Integration: Work closely with product teams to seamlessly integrate ML capabilities into customer-facing features, ensuring technical excellence translates into user value and product differentiation * Optimize AI Agent Performance: Continuously improve our AI agents through systematic experimentation, prompt engineering, and architectural enhancements, measuring success through customer impact and system performance * Scale ML Infrastructure: Build the foundational ML systems, monitoring, and tooling that will support our growth from startup to scale, ensuring we can deploy new capabilities quickly without compromising quality * Partner with Engineering Leadership: Collaborate directly with our CTO through regular check-ins and strategic alignment while operating with high autonomy and self-direction in day-to-day execution * Mentor Through Excellence: Provide natural mentorship to junior ML engineers through code reviews, technical guidance, and sharing practical experience from building production ML systems WHAT YOU NEED TO BE SUCCESSFUL: * Proven Production ML Experience: 6+ years building and scaling machine learning systems in production environments, with hands-on experience moving from experimentation to customer-facing deployments * Deep Neural Networks Foundation: Strong background in classical neural networks and deep learning fundamentals before specializing in modern LLMs and transformer architectures - you understand the foundations, not just the latest tools * Product-Focused ML Mindset: Experience building ML systems that solve real business problems, with a track record of integrating classification, prediction, or recommendation systems into actual products customers use * Multi-Company Perspective: Experience across multiple organizations (scale-ups, startups, or combination), giving you practical knowledge of what tools to build vs buy and how to avoid over-engineering * Technical Versatility: Strong Python skills with flexibility across ML frameworks and tools - comfortable adapting to our stack including LangChain, evaluation frameworks, and workflow orchestration tools like Temporal * Self-Directed Leadership: Ability to operate autonomously while maintaining close alignment with leadership, comfortable with frequent check-ins but capable of driving projects independently * Cross-Functional Collaboration: Experience working closely with product teams and potentially customers, translating technical capabilities into business value and user experiences * Nice to Haves: * Experience with AI agents, LLMs, or modern generative AI applications * Cybersecurity domain knowledge or experience applying ML to security challenges * Background at ML-first companies or organizations where ML was core to the product * Experience with modern MLOps practices and cloud-based ML infrastructure * Track record of optimizing model performance and controlling AI system costs WHY JOIN US: * Real-World AI Impact: Drive the actual productionization of LLMs and machine learning to solve significant cybersecurity pain points - your work will directly protect organizations from real threats, not just optimize internal metrics * Technical Leadership Opportunity: Work directly with our CTO on cutting-edge ML infrastructure while having the autonomy to shape technical decisions and build systems that scale with our hypergrowth * Expert Team Partnership: Join a team of hands-on leaders with experience in Big Tech and Scale-ups, including leadership team members who have been part of multiple acquisitions and an IPO * Build the AI-Native Future: Shape how generative AI transforms cybersecurity from the ground up, establishing ML practices and technical standards that will define the industry * Multiple Growth Pathways: Clear opportunities to grow into Head of ML Engineering, become a domain technical lead, move into customer-facing technical roles, or excel as a senior individual contributor - the choice is yours based on your interests and our needs * Breakthrough Technology: Work at the intersection of generative AI and cybersecurity, building solutions that leverage the latest advances in LLMs and AI agents to solve some of the most pressing challenges security teams face today

Honor Technology’s mission is to change the way society cares for older adults. As a leader in aging care innovation, Honor provides the technology, tools, and services that empower older adults to live life on their own terms. Honor’s growing portfolio includes its consumer care brand, Home Instead, Inc., the world’s leading provider of in-home care for older adults. With a global franchise network and more than 100,000 Care Pros, Home Instead delivers over 50 million hours of personalized care annually. Together, Honor and Home Instead are setting a new standard for aging in place, backed by powerful technology, compassionate care, and a commitment to aging on your own terms. Join us to create a new and better aging experience for our clients, their families, and our Care Professionals.  ABOUT THE WORK This position is on our Applied AI team, which is responsible for helping Honor safely and pragmatically apply AI across our operating model, product systems, and internal workflows. The mission of the Applied AI team is to help Honor become an organization that learns faster, remembers more, and continuously compounds what it learns over time. We believe the most valuable use of AI at Honor is not isolated task automation, but building durable organizational intelligence: systems that retain operational context, surface relevant prior learning, support better decisions, and help teams turn fragmented insights into repeatable improvements. Honor operates in a deeply relationship-driven industry. The best home care operators personalize service because they remember the details, understand context, and adapt to the situation. At Honor’s scale, that requires thoughtful systems: reliable context, governed access, reusable AI patterns, traceable workflows, and product experiences that help humans and agents make better decisions together. As a Senior Engineer on Applied AI, you will help design, build, and productionize the foundations that make this possible. You may work on systems that power AI-assisted sales follow-up, operational defect analysis, reusable memory and retrieval patterns, internal agentic tools, AI-powered data analysis, schedulable workflows, or closed-loop feedback systems that connect audits, product changes, and measurable business outcomes. You will work closely with engineering, product, design, data, operations, security, and business stakeholders to move quickly while maintaining the discipline needed for production systems. This team is highly exploratory, but the work is not a lab exercise. We are looking for engineers who can turn ambiguous AI opportunities into safe, reliable, measurable product and platform capabilities. We have an exciting runway ahead of us. As AI becomes an operational layer across Honor, we need engineers who can help create the paved roads: secure model access, compliant data pathways, observability, cost controls, evaluation patterns, human-in-the-loop workflows, and reusable architecture that allows teams across Honor to adopt AI without creating long-term fragmentation. ABOUT YOU * You thrive in a diverse, cross-functional team, collaborating with design, product management, data, operations, security, and other engineering teams. * You are excited by ambiguous, high-leverage problems where the right answer requires both technical judgment and operational empathy. * You enjoy building production-grade systems that connect user-facing workflows, backend services, data pipelines, and AI/LLM capabilities. * You’ve built and maintained production-grade features in Python, or have transferable experience in common languages like Node.js and are willing to learn Python. * You know how to design reliable data models and have used relational databases at scale. * You have been a key contributor to the design and implementation of large, complex projects. * You are comfortable working in and refactoring legacy, monolithic systems while also designing new services and integration patterns. * You are a strong communicator, both verbally and in writing, and can explain technical tradeoffs to technical and non-technical audiences. * You think carefully about quality, observability, privacy, security, and operational risk. * You are excited to work with AI systems in a way that is pragmatic, measurable, and grounded in real business outcomes. * You are willing to participate in an on-call rotation in collaboration with our tier 1 support team. SOME, OR ALL, OF THESE ARE TRUE * You have experience building LLM-powered products, AI agents, retrieval systems, memory systems, or evaluation frameworks. * You have worked with model providers or platforms such as AWS Bedrock, OpenAI, Gemini, Anthropic, or similar systems. * You have experience with secure data access patterns, RBAC, auditability, or compliant data workflows. * You have built internal tools, workflow automation, or systems that support operations teams at scale. * You are comfortable working with messy operational data and turning it into reliable product or platform capabilities. * You have experience designing systems that involve human-in-the-loop review, feedback loops, or measurable quality improvement. * You are knowledgeable about microservice architecture and best practices. * You have experience working with an RPC architecture. * You are comfortable with frontend development and have experience with JavaScript frameworks like React. * You have experience leveraging observability and monitoring tools like DataDog. * You enjoy mentoring and spreading knowledge to other engineers. * You are energized by building foundations that help other teams move faster and more safely. TECH YOU MAY USE * Python * Thrift * MySQL * AWS * AWS Bedrock * OpenAI, Gemini, Anthropic, or similar model platforms * JavaScript * React * Looker * GitHub * DataDog * Internal agentic tools and workflow automation platforms   #LI-Remote Our range reflects the hiring range for this position.  We use national average to determine pay as we are a remote first company.  Individual pay is based on a number of factors including qualifications, skills, experience, education, and training. Base pay is just a part of our total rewards program.  Honor offers generous equity packages that increase with position level and responsibilities, and a 401K with up to a 4% employer match. We provide medical, dental and vision coverage including zero cost plans for employees.  Short Term Disability, Long Term Disability and Life Insurance are fully employer paid with a voluntary additional Life Insurance option.  We offer a generous time off program, mental health benefits, wellness program, and discount program.   Hiring Salary Range $160,000—$180,000 USD At Honor, we put people first. Our leadership culture is guided by Leadership Principles that prioritize integrity, compassion, and excellence. We offer a unique opportunity to lead with purpose and make a meaningful impact no matter your role. Honor is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex (including pregnancy), national origin, age, disability, genetic information, political affiliation or belief.

Summary of the Role: As an Engineer at Maze, you'll play a pivotal role in shaping our product, with significant focus on the development of AI Agents and ML systems. You will have the unique opportunity to design, build, and scale a product from the ground up, influencing everything from architecture decisions to ML integrations and the overall user experience. This is an exciting chance to be at the core of our technical team, driving innovation in AI-powered cybersecurity solutions and ensuring seamless integration across the stack. Your Contributions to Our Journey: * AI Agents: Play a pivotal role in the development and scaling of complex AI Agents to tackle some of the biggest challenges in cybersecurity. * Architect and Develop: Design and implement backend systems that effectively support agentic workloads, ensuring they are scalable, maintainable, and secure. * End-to-End Ownership: Take ownership of the entire development lifecycle, from concept and design to deployment and maintenance. * Integrate Seamlessly: Work closely with other engineers, our designer/product manager to ensure seamless integration of new features and services. * Optimize for Performance: Continuously monitor and improve application performance, security, and scalability. * Establish Best Practices: Define and enforce coding standards, best practices, and documentation to maintain high code quality. * Rapid Prototyping: Quickly prototype and iterate on new features, adapting to user feedback and changing requirements. * Mentor and Lead: As the team grows, mentor junior engineers and lead by example in technical discussions and code reviews. What You Need to Be Successful: * Extensive Experience: 7+ years of experience in backend development * Backend Mastery: Strong experience with backend development, including RESTful API design, database management, and server-side frameworks (e.g., Python). * ML/AI Understanding: Working knowledge of machine learning principles and experience integrating LLMs or other AI services into production applications. Familiarity with tools like LangChain, LlamaIndex, or similar frameworks is a plus. * Cloud Experience: Familiarity with cloud platforms (e.g., AWS) and their ML services, along with DevOps practices, including CI/CD and containerization (e.g., Docker, Kubernetes). * Problem-Solving Skills: Strong analytical and problem-solving abilities, with a focus on delivering robust and scalable solutions. * AI Systems Architecture: Understanding of how to architect systems that effectively leverage AI capabilities while maintaining performance and reliability. * Collaborative Spirit: Excellent communication skills and the ability to work effectively in a cross-functional team. * Agility and Adaptability: Comfort working in a fast-paced startup environment with the ability to pivot and adapt as needed, particularly in the rapidly evolving AI landscape. Why Join Us: * Ambitious Challenges: We are using Generative AI (LLMs and Agents) to solve some of the most pressing challenges in cybersecurity today. You’ll be working at the cutting edge of this field, aiming to deliver significant breakthroughs for security teams. * Expert Team: We are a team of hands-on leaders with deep experience in Big Tech and Scale-ups. Our team has been part of the leadership teams behind multiple acquisitions and an IPO. * Impactful Work: Cybersecurity is becoming a challenge to most companies and helping them mitigate risk ultimately helps drive better outcomes for all of us.