Why This Job is Featured on The SaaS Jobs
This role stands out for SaaS-minded engineers because it sits at the boundary between research-grade prototypes and production-quality systems, a transition point that many SaaS companies face when turning novel capabilities into dependable product features. While the work is framed around sensing and on-device constraints rather than a classic web stack, the underlying engineering themes map closely to shipping customer-facing software that must behave predictably under real-world variability.
Long term, the role builds durable SaaS-adjacent skills in reliability, observability, performance engineering, and interface design, all of which become more valuable as products scale and teams multiply. The emphasis on integration surfaces, evaluation hooks, and quality guardrails mirrors how mature SaaS organizations operationalize experimentation and reduce risk when deploying new functionality. Cross-functional debugging across algorithms and systems also develops the kind of end-to-end ownership that translates well to platform and infrastructure work inside SaaS environments.
It is best suited to engineers who prefer craft and rigor over purely exploratory work, and who enjoy making ambiguous technical ideas measurable, testable, and maintainable. It will fit someone comfortable collaborating across disciplines and iterating on tooling and pipelines until they are resilient enough for repeated, production-like use.
The section above is editorial commentary from The SaaS Jobs, provided to help SaaS professionals understand the role in a broader industry context.
Job Description
About the Team
Consumer Products Research prototypes the future of computing: we explore new modalities, interaction patterns, and system behaviors, then do the engineering required to make those ideas real in rigorous prototypes. The Neosensing team sits at the intersection of sensing, edge algorithms, and systems engineering. We build the end-to-end software that turns new signals into dependable capabilities—collection tooling and protocols, algorithm integration and evaluation hooks, and on-device loops that stay stable under real-world variability. We care deeply about software quality and iteration speed: clean interfaces, debuggability, observability, and performance under tight device constraints.
About the Role
As a Software Engineer on Consumer Products Research, you’ll sit at the boundary between algorithm development and shippable systems. You’ll work closely with algorithm engineers to translate prototypes into clean interfaces, reliable pipelines, and efficient on-device implementations—with strong attention to performance, observability, and real-world failure modes.
This is a software role first: we’re looking for someone who loves writing great code every day, takes pride in engineering craft, and is comfortable going deep enough into the algorithmic details to make the system work end-to-end.
This role is based in San Francisco, CA. We use a hybrid work model of four days in the office per week and offer relocation assistance to new employees.
In this role, you will:
Build and ship production software for sensing algorithms, translating algorithm prototypes into reliable end-to-end systems.
Implement and own key parts of the Python shipping pipeline (integration surfaces, evaluation hooks, and quality/performance guardrails).
Develop embedded/on-device software in an RTOS environment (e.g., Zephyr) and deploy models to device runtimes and hardware accelerators.
Optimize real-time on-device perception loops (e.g., detection/tracking-style pipelines) for stability, latency, power, and memory constraints.
Create data collection + instrumentation tooling to bring up new sensing modalities and accelerate iteration from prototype → dataset → model → device.
Partner cross-functionally (algorithms, human data, firmware/hardware) to debug, profile, and harden systems against real-world variability.
You might thrive in this role if you:
Love writing great software and want your work to sit close to novel sensing and edge algorithms.
Understand algorithm behavior well enough to integrate, debug, and evaluate it—even if you’re not the primary model inventor.
Have shipped production Python systems and care about clean interfaces, tests, and long-term maintainability.
Enjoy embedded/on-device work and can debug across hardware, firmware, and higher-level application layers.
Care about performance engineering and know how to profile and optimize under tight device constraints.
Take ownership end-to-end and thrive in ambiguous, fast-moving, zero-to-one environments.
Bonus:
Zephyr (or similar RTOS) experience.
On-device ML deployment (NPU/GPU/DSP) and accelerator-aware profiling/optimization.
Background in multimodal sensing, sensor fusion, or on-device perception.
Experience building data collection systems and human-in-the-loop workflows (protocols, QA, metadata)
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.
We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.
For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
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