Zuma is pioneering the future of agentic AI in property management. We build AI agents that act as property managers, handling the full spectrum of interactions with both prospects and current residents on behalf of our clients.

Our agents don’t just assist human workflows; they own them end-to-end, operating across leasing, collections and resident communications. Zuma has ambitions to continue expanding into adjacent work activities in tangential areas of property management.

This is a rare chance to shape the future of how an entire industry operates , not in theory, but in production, at scale, touching real customers and physical assets every day. At Zuma, human and AI agents work side by side, and you'll help define what that collaboration looks like at its best.

Responsibilities

• Own E2E projects that cross all areas of software development including full stack web apps, agentic AI solutions across multiple work activities, extensive integrations with PMS and CRM systems, infrastructure, and internal tooling.

• Architect, build, and deploy production AI agents using modern agent frameworks, owning the full lifecycle from design to reliability in production.

• Define the technical patterns and standards for how software is built across the engineering org , you will be setting the playbook others follow.

• Strengthen our core systems , including our onboarding/configuration system, integration frameworks, and AI performance analytics infrastructure.

• Collaborate directly with the VPE and product leadership to translate product vision into delivery, making high-stakes technical trade-offs with confidence.

• Own system reliability, observability, and continuous improvement , defining how we measure, monitor, and iterate on our agents and web products in production.

• Work across the stack (backend services, LLM orchestration, integrations, data pipelines, frontends) to ship agents and products that are robust and scalable.

• Tame legacy code and lay down new foundations , patterns and architecture you create will be inherited by the engineers who come after you.

• Be a close partner to the product and operations teams, turning their domain needs into intelligent automated workflows without requiring domain expertise upfront.

Nice to Have

• Prior experience at a startup or high-growth company; comfort shipping fast and iterating in production.

• AWS experience with IaC (Terraform) and comfort working with infrastructure / dev ops.

• Background in building self-serve platforms or integration infrastructure.

• Experience with workflow automation platforms or business process orchestration.

• Experience with telephony integrations (Twilio or similar) and building voice-capable agents or chatbots across text and voice channels.

• Familiarity with speech-to-text, text-to-speech, or real-time audio streaming pipelines in production AI systems.

• Classical ML experience , supervised/unsupervised learning, feature engineering, model training and evaluation outside of LLM contexts.

Our Stack

• Python, TypeScript/Node.js

• OpenAI, Anthropic

• LangGraph, OpenAI Agents SDK, custom orchestration layers

• AWS, AWS ECS, PostgreSQL, Redis

• RealPage, Entrata, Yardi, and other property management systems

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Research Engineer, Notifications

Location

San Francisco

Employment Type

Full time

Department

Applied AI

Compensation

• $295K – $680K • Offers Equity

The base pay offered may vary depending on multiple individualized factors, including market location, job-related knowledge, skills, and experience. If the role is non-exempt, overtime pay will be provided consistent with applicable laws. In addition to the salary range listed above, total compensation also includes generous equity, performance-related bonus(es) for eligible employees, and the following benefits.

• Medical, dental, and vision insurance for you and your family, with employer contributions to Health Savings Accounts

• Pre-tax accounts for Health FSA, Dependent Care FSA, and commuter expenses (parking and transit)

• 401(k) retirement plan with employer match

• Paid parental leave (up to 24 weeks for birth parents and 20 weeks for non-birthing parents), plus paid medical and caregiver leave (up to 8 weeks)

• Paid time off: flexible PTO for exempt employees and up to 15 days annually for non-exempt employees

• 13+ paid company holidays, and multiple paid coordinated company office closures throughout the year for focus and recharge, plus paid sick or safe time (1 hour per 30 hours worked, or more, as required by applicable state or local law)

• Mental health and wellness support

• Employer-paid basic life and disability coverage

• Annual learning and development stipend to fuel your professional growth

• Daily meals in our offices, and meal delivery credits as eligible

• Relocation support for eligible employees

• Additional taxable fringe benefits, such as charitable donation matching and wellness stipends, may also be provided.

More details about our benefits are available to candidates during the hiring process.

This role is at-will and OpenAI reserves the right to modify base pay and other compensation components at any time based on individual performance, team or company results, or market conditions.

About the Team

The ChatGPT team works across research, engineering, product, and design to bring OpenAI’s technology to the world.

We seek to learn from deployment and broadly distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. We aim to make our innovative tools globally accessible, transcending geographic, economic, or platform barriers. Our commitment is to facilitate the use of AI to enhance lives, fostered by rigorous insights into how people use our products.

About the Role

We are looking for a Machine Learning Engineer to join our Notifications team, focused on building and scaling intelligent notification systems that provide real value to users even when they are not actively on the product. This role will be central to shaping how ChatGPT communicates proactively and helpfully with users—surfacing the right content, at the right time, through the right channel.

You will work on designing and implementing ranking and recommendation systems that leverage both classical ML techniques and large language models (LLMs) to optimize notification relevance, timeliness, and user experience. The ideal candidate has strong ML fundamentals, experience shipping ranking or recommendation systems in production, exposure to LLMs, and sharp product intuition. You should be comfortable operating across research and product boundaries: thinking from first principles, running rigorous experiments, and building scalable systems.

This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees.

In this role, you will:

• Design and build end-to-end ranking and recommendation systems for notifications, from modeling to evaluation and deployment.

• Apply and adapt LLMs to ranking problems, including prompt-based approaches and fine-tuning.

• Develop experiments to evaluate notification relevance, user value, and long-term impact, working closely with product, data science, and engineering teams.

• Collaborate with research teams to leverage the latest modeling techniques while balancing practical constraints of production systems.

• Build robust offline and online evaluations to measure system improvements and user outcomes.

• Contribute to the broader Growth ML stack and help set technical direction for intelligent user engagement systems.

You might thrive in this role if you:

• Have hands-on experience building and deploying ranking, recommendation, or personalization systems at scale.

• Have a deep understanding of machine learning and its applications, with exposure to LLMs and their integration into product experiences.

• Are experienced in experimentation, A/B testing, and analyzing impact on user behavior and business metrics.

• Are comfortable diving into large ML codebases, designing evaluations, and debugging complex modeling issues.

• Thrive in dynamic, fast-changing environments and can think from first principles to design elegant solutions.

• Have strong product intuition and can balance modeling sophistication with product impact.

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

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