Senior Machine Learning Engineer - Recommendation & AI Applications

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 are looking for a Senior Machine Learning Engineer to help evolve our large-scale recommendation systems and apply AI / LLM technologies to real-world production problems. You will work on core feed, retrieval, and ranking systems serving tens of millions of users, while also participating in AI-driven innovation projects that explore new ways to improve content discovery, personalization, and developer productivity. This role is ideal for engineers who enjoy strong individual ownership, hands-on development, and translating ideas into reliable systems.

 What You’ll Work On

Large-Scale Recommendation Systems

• Design, build, and iterate on high-throughput, low-latency recommendation systems powering NewsBreak’s core feeds.
• Improve retrieval, ranking, and multi-objective optimization to balance engagement, retention, content quality, and business metrics.
• Own systems from offline training → online inference → A/B experimentation → metric analysis.
• Identify and resolve issues related to data quality, model drift, and system performance in production.

AI & LLM Applications

• Apply LLMs and foundation models to recommendation-related problems such as content understanding, user intent modeling, and feature generation.
• Prototype quickly, validate with experiments, and push successful ideas into production.

AI-Driven Development

• Embrace AI-assisted development workflows, including LLM-powered coding, debugging, and analysis.
• Apply AI across feature ideation, prototyping, and experiment analysis.

0 → 1 Innovation

• Contribute to 0–1 AI-powered projects, helping take ideas from early exploration to MVP and production.

What We’re Looking For

Minimum Qualifications - 3+ years of industry experience building machine learning or recommendation systems in production. - Strong understanding of recommendation system fundamentals (ranking, embeddings, user/item modeling, experimentation). - Strong coding skills with Python / Java / Scala, and experience with PyTorch or TensorFlow. - Experience working with large-scale data and ML systems (e.g., Spark, distributed training, real-time inference). - Ability to own features end-to-end and deliver measurable business impact.

Bonus / Plus Qualifications - Production experience applying AI or LLMs to recommendation systems. - Experience contributing to 0 → 1 AI or ML-driven products. - Familiarity with AI-assisted development tools and workflows.

Benefits

We offer a competitive benefits package:

• Health, dental, and vision care for you and your family (100% coverage for employee)
• Top-tier 401(K) plan with company matching
• Paid time off and paid holidays
• FSA, HSA and commuter benefits programs
• Team activity budget

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