SDE-1, AI Engineer

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Zinier

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Job Summary


Job Type
-

Seniority

Years of Experience
Information not provided

Tech Stacks
Python PyTorch Go

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

  • 2–4 years of experience in software engineering with at least 2 years working on AI/ML-based systems.
  • Building chatbots, copilots, or automation tools
  • Integrating LLMs into products (e.g., support automation, content generation)
  • 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.

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