Software Engineer, ML Infra
Mountain View, California, United States
- Pay
USD 180,000–225,000/year · Base — pay source
Annual Base Pay Range $180,000—$225,000 USD CPRA Privacy Notice for California Candidates
Read the full posting- Work setting
- Not stated
- Employment
- Not stated
What you’ll work on
Full postingWe’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 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.
Design and develop machine learning infrastructure
Own core ML systems for offline and online training, serving, and features
Proactively fix ML infrastructure issues that could affect production
Work with ML engineers to build model pipelines on the infrastructure
From the employer’s posting
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.
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.
What you’ll bring
All qualificationsCore experience
- Experience delivering production systems that support ML use cases (training or serving).
- Proficient in Python, with a strong understanding of object-oriented languages such as C++ or Java
Preferred experience
- Experience leading cross-team projects from design through stable rollout.
- Experience iterating on ML models and shipping them to production.
Qualification wording
Experience delivering production systems that support ML use cases (training or serving).
Proficient in Python, with a strong understanding of object-oriented languages such as C++ or Java
Experience leading cross-team projects from design through stable rollout.
Experience iterating on ML models and shipping them to production.
Education & alternatives
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).
Tools in this posting
- C++
- Java
- Python
Source — Tool mentions in context
- 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
Benefits in the posting
Full benefits wording- 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
- The US base salary range for this full-time position is listed below. Pay may vary based on a number of factors including job-related skills, level, experience, geographic location and relevant education or training. At NewsBreak, we design our overall rewards package to attract top talents. Depending on the position, the role may also be eligible for discretionary bonus and options. Your recruiter can share more details during the hiring process.
- Annual Base Pay Range
- CPRA Privacy Notice for California Candidates
From the employer’s posting.
About NewsBreak
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.
In the employer’s words · Read in context
Posting record
Report an errorOpen 6 monthsWe first saw this posting 197 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Apr 15, 2026 · 197 days ago
- Recorded sightings
- 142
- Last seen by us
- Oct 29, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
Your next step
- Have your resume and examples of relevant work ready.
- Check the listed location, eligibility and core experience before starting.
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Job description
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
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Annual Base Pay Range $180,000—$225,000 USD CPRA Privacy Notice for California Candidates
- Location & working pattern
Mountain View, California, United States
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.
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