Software Engineer, ML Infra
At a glance
Mid-level ML Platform & Ops role at NewsBreak. Mountain View · $180,000–$225,000 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Build infrastructure that supports model training, serving, feature work and pipeline health checks
- Make offline and online model training run faster and with greater reliability
- Improve serving speed and keep features and embeddings consistent between offline and live systems
- Find and fix infrastructure problems that could put production at risk
- Work with ML engineers to create reliable model pipelines on the infrastructure
What you bring
- A related bachelor's degree with at least five years of relevant experience, or a related master's or doctoral degree with at least three
- Experience shipping production systems for machine-learning training or serving
- A record of building and maintaining distributed backend systems at large scale
- Python skills and familiarity with object-oriented programming, including C++ or Java
Who this fits
This role suits an engineer who wants to own production infrastructure across the ML lifecycle. You'll join a small team and work with product, data and ML colleagues. The position is based in Mountain View.
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
- Education: Bachelor's degree in a related field with 5+ years of relevant experience, or MS/PhD in a related field with 3+ years of relevant experience
- Experience delivering production systems that support ML use cases (training or serving).
- Proven track record in building and maintaining large-scale distributed backend systems
- Proficient in Python, with a strong understanding of object-oriented languages such as C++ or Java
- Strong problem solving skills with good teamwork and communication skills
Preferred qualifications
- Experience leading cross-team projects from design through stable rollout.
- Experience iterating on ML models and shipping them to production.
Benefits
We offer competitive benefits package:
- Health, dental, and vision care for you and your family
- Top-tier 401(K) plan with company matching
- Paid time off and paid holidays
- Paid parental leave
- FSA and commuter benefits programs
- Team activity budget
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