Software Engineer, ML Infra (Junior & New Grad)
At a glance
Junior ML Platform & Ops role at NewsBreak. Mountain View · $125,000–$175,000 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Build the systems that train, serve and track models used by Ads and Recommendations
- Improve offline and online training, pipeline health monitoring, model delivery, and feature creation and delivery
- Spot infrastructure faults that could affect live services and take steps to resolve them
- Help ML engineers create dependable model pipelines with the infrastructure you maintain
What you bring
- A related bachelor's degree and at least two years of relevant work, or a graduate degree in a related discipline
- You write Python proficiently and understand object-oriented programming in C++ or Java
- You have introductory applied ML knowledge and have used frameworks such as PyTorch or TensorFlow
- You are familiar with source control, issue tracking and writing design documentation
Who this fits
This junior role suits an engineer who wants hands-on ownership of production ML infrastructure and works closely with ML engineers. The position is based in Mountain View, California.
From the employer
About NewsBreak
Local life runs on local information. What happened down the street? Who can fix this? Where should we go tonight? NewsBreak started in 2015 to answer these questions, and today more than 40 million people a month rely on us to follow what’s going on in their zip code.
Three platforms with one vision: powering local life. Led by founder and CEO Jeff Zheng, NewsBreak is our local life and news platform; Nearby AI connects people with local businesses; and NDot AI helps publishers and creators grow and earn.
Building for the long term. A $115 million Series C made us a unicorn in 2021, and we keep investing in our people. We’re Great Place to Work® certified and named to Fast Company’s Best Workplaces for Innovators (2025) and Fortune’s Best Workplaces in the Bay Area™ (2026).
Everyone makes an impact. Whether you write code, shape products, tell our story, or run the business, we want people who own projects end to end, stay curious, and speak up. Join us.
Learn more at: NewsBreak, Nearby AI, NDot AI
About the role:
We’re hiring a Machine Learning Infrastructure Engineer to help build the backbone that trains, serves, and monitors the models behind our Ads and Recommendations products. You’ll join a small, high-ownership team that ships platform improvements end-to-end—partnering with product and data teams, reducing latency and cost, and shortening the path from an idea to a safely launched model.
You’ll work across the ML lifecycle: making training faster and more reliable, improving model serving performance, and strengthening our feature/embedding platform so models stay fresh and consistent between offline and online use. We’re looking for someone who can take real ownership, finish what’s started, and raise the bar on stability and developer experience.
Why this role
- Scope & impact: small team, big surface area—your work lands directly in production.
- Ownership: from design to rollout to post-launch learnings; real autonomy with support.
- Growth: visibility across the stack and a clear path to lead projects and mentor others.
- Pragmatic culture: we optimize for outcomes over buzzwords, and we value clear thinking, and follow-through.
If you like building reliable systems that make ML teams move faster—and you enjoy turning complexity into simple, durable solutions—we’d love to talk.
Responsibilities
- Design and develop machine learning infrastructure.
- Own and enhance core components of the ML infrastructure, including systems for offline and online model training, model pipeline health monitoring, model serving, feature authoring, and feature serving.
- Proactively address ML infrastructure issues that may impact production.
- Collaborate with ML engineers to build robust model pipelines utilizing the ML infrastructure.
Requirements
- Bachelor’s degree in Computer Science, Engineering, or a related field with 2+ years of relevant work experience; or a Master’s/PhD in a related discipline.
- Familiarity with software development processes, including version control, bug tracking, and design documentation.
- Proficient in Python, with a strong understanding of object-oriented languages such as C++ or Java
- Basic knowledge of Applied Machine Learning and experience with major Deep Learning frameworks, such as PyTorch and TensorFlow.
Preferred qualifications
- Familiarity with cloud services such as AWS, GCP, Azure, and others.
- Contributions to open-source machine learning or infrastructure tools.
- A systematic, data-driven problem-solving approach combined with strong communication skills.
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