Why This Job is Featured on The SaaS Jobs
Zinier operates in a vertical SaaS category—field service automation—where product value is tightly linked to real-world operations and measurable outcomes. Featuring an AI Engineer here highlights how SaaS companies are increasingly embedding machine learning directly into core workflows, not as a standalone lab function. The listing also signals a platform mindset: AI is expected to ship as services, integrate with existing product components, and hold up under production constraints.
From a SaaS career standpoint, the role concentrates on end-to-end delivery: models, data pipelines, APIs, deployment workflows, and ongoing optimization. That combination is especially transferable across subscription software businesses, where reliability, iteration speed, and cost/performance trade-offs matter as much as model quality. Working close to architecture discussions and code review loops is also a practical path toward broader technical leadership in AI-enabled SaaS products.
This role suits engineers who prefer fundamentals-driven problem solving and want ownership across the AI lifecycle rather than focusing only on experimentation. It aligns with professionals comfortable navigating product-grade constraints—latency, scalability, monitoring, and maintainability—while collaborating with senior engineers to turn ML capability into durable software components.
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
Who we are:
Zinier’s No-Code Customization field service automation platform empowers field service organizations with the combined power of humans and technology to keep our world up and running.
No two field service organizations are alike…
From the IT ecosystem you connect with, to the workflows executed in the field, your business requirements are unique. And in the fast-paced world of field service, those requirements can change rapidly. And that’s exactly why you need Zinier.
ZiniApps solve challenges across the entire lifecycle of field work. Off-the-shelf functional, but also customizable to meet specific use cases, ZiniApps cover the most meaningful jobs to be done in field service installation and maintenance.
We are a global team headquartered in Silicon Valley with leading investors including Wipro, Telmex, Black & Veatch, NCR, Toshiba and Qualcomm Ventures LLC.
To learn more, check out www.zinier.com
Why we exist:
Services shape how we live. Electricity lights up our homes. The Internet opens up our worlds. Cellular phones keep us connected no matter where we are. We take for granted the things we can turn on with the flip of a switch. But when even one of the services we depend on isn’t available, the day can quickly start to go sideways.
For organizations that provide these services, some of the most important work happens in the field — in neighborhoods, across open spaces, and along millions of last miles that criss-cross the country. Every moment of downtime matters, which is why Zinier exists. Zinier empowers organizations to work smarter — from the main office to the field — to solve problems quickly, fix things before they break, and keep people in the rhythm of their days.
To do this, Zinier has created a scalable platform powered by AI-driven insights and intelligent automation that helps field service teams work smarter, better, faster, and more efficiently. We help organizations automate routine tasks so the people in the field can focus on putting their expertise to work. We work with customers in telecom and energy.
Role Overview
We are seeking a highly motivated AI Engineer with strong fundamentals in machine learning and system design. This role is ideal for someone who enjoys building end-to-end AI services, understands the mathematics behind models, and thinks deeply about performance, scalability, and efficiency—beyond just applying pre-built tools. You will be part of the initial AI core team of engineers driving the AI initiatives at Zinier.
Key Responsibilities
- Design, build, and maintain end-to-end AI/ML services and components.
- Develop, train, fine-tune, and evaluate AI/ML models for real-world use cases.
- Contribute to the development of production-grade AI systems, including data pipelines, APIs, and deployment workflows.
- Work closely with senior engineers and AI leaders to implement robust and scalable solutions.
- Analyze model behavior and performance from a low-level, fundamentals-driven perspective.
- Participate in architecture discussions, code reviews, and continuous improvement initiatives.
- Debug, optimize, and enhance AI models and systems for accuracy, efficiency, and reliability.
Required Qualifications
- 3–5 years of experience in software engineering with at least 2 years working on AI/ML-based systems.
- Hands-on experience building or contributing to end-to-end services or AI-driven products.
- Strong understanding of machine learning fundamentals, including mathematical and statistical concepts.
- Ability to reason about systems from first principles (data, algorithms, compute, memory) rather than only application-level abstractions.
- Proficiency in at least one AI/ML framework (e.g., PyTorch, TensorFlow).
- Solid programming skills in Python and/or other relevant languages.
Nice to Have
- Experience deploying models to production environments.
- Familiarity with distributed systems, cloud platforms, or MLOps tools.
- Exposure to optimization techniques, model efficiency, or performance tuning.
