---
title: 'Machine Learning Engineer, LLM Post-Training at NewsBreak'
canonical: 'https://feeny.ai/job/machine-learning-engineer-llm-post-training-newsbreak-mountain-view-california-a88f39nqqfaa'
type: 'job'
last_seen: '2026-09-07'
---

# Machine Learning Engineer, LLM Post-Training at NewsBreak

- **Company:** NewsBreak
- **Location:** Mountain View California, United States
- **Compensation:** $150k–$230k
- **Posted:** 2026-06-10
- **Last confirmed live:** 2026-09-07
- **Apply:** https://job-boards.greenhouse.io/newsbreak/jobs/4688409006

## Job description

## About NewsBreak

Founded in 2015, NewsBreak is the Content Intelligence platform shaping the future content economy. With over 40 million monthly active users, our flagship platform delivers highly personalized local news and information powered by advanced AI, recommendation systems, and adtech.

Recognized by Fast Company as #32 on the Top Workplaces for Innovators, we're proud to be Great Place to Work® certified and home to a dynamic team of technologists, product innovators, and business leaders who are passionate about solving meaningful challenges at scale.

Together, we reached unicorn status in 2021, and we remain committed to continuing this high-growth trajectory with the right team to fulfill our mission: building the infrastructure layer for content intelligence.

If you’re inspired to dream big, innovate fast, and make a difference, we’d love to hear from you! For more information, visit [www.newsbreak.com/about](http://www.newsbreak.com/about)

## About the Role

We are looking for a hands-on Machine Learning Engineer to drive the post-training of our large language models, with a strong emphasis on reinforcement learning (RL). You will own the full post-training stack — continuous pre-training (CPT), supervised fine-tuning (SFT), and RL — along with the data preparation that powers it. Just as important, you will work directly with product and business teams to translate real-world use cases into concrete training objectives and ship model improvements quickly. This is a high-ownership role for someone who has actually trained models, not just read about it.

## Responsibilities

- Lead post-training of our LLMs across the full pipeline: continuous pre-training, SFT, and reinforcement learning, with RL as the primary focus (e.g., RLHF, PPO, GRPO, DPO, and related methods).
- Design, build, and curate the data that drives each training stage — instruction/SFT datasets, preference pairs, reward signals, on-policy rollouts, and rejection-sampled completions — and define data-preparation strategies tailored to specific business needs.
- Partner closely with business and product stakeholders to understand their scenarios, rapidly convert requirements into training plans, and deliver targeted model capabilities on tight timelines.
- Run large-scale training on mid-to-large GPU clusters, applying distributed-training techniques (data parallelism, FSDP, and where relevant tensor/pipeline parallelism) and tuning for throughput and stability.
- Build and maintain evaluation and reward/verifier pipelines to measure model quality, prevent regressions, and ensure training–serving consistency.
- Stay current with post-training research and turn promising techniques into working, production-ready code.

## Requirements

- Hands-on LLM post-training experience. You have personally run CPT, SFT, and RL training — with demonstrated, practical RL experience (RLHF / PPO / GRPO / DPO or similar), beyond just launching training scripts.
- Strong data engineering for ML. You can independently design data-preparation plans for a given business scenario — sourcing, cleaning, filtering, labeling strategy, and synthetic/preference data generation — to meet specific product requirements.
- Proven large-scale GPU training ability. You have trained LLMs on mid-to-large GPU hardware and are comfortable with distributed training and debugging at scale.
- Strong PyTorch fundamentals; working familiarity with frameworks such as Hugging Face TRL/Accelerate, DeepSpeed or FSDP, and inference engines like vLLM.
- Solid understanding of tokenization, attention, chat templates, and common failure modes in alignment/agent training.
- A bias toward fast iteration and business impact, with strong communication skills to work across research and product teams.

## Preferred Qualifications

- Experience designing reward models or rule-based verifiers for RL.
- Experience with tool-use / agentic model training (function calling, multi-step planning).
- Publications or open-source contributions in LLM post-training or RL.

## 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

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 $150,000—$230,000 USD

[CPRA Privacy Notice for California Candidates](https://docs.google.com/document/d/15apsJLgHq1p5NJR3fzFmdctKX4QIzzf2/edit?usp=sharing&ouid=110601223912453011659&rtpof=true&sd=true)

## About NewsBreak

## Company Overview
- **One-liner**: NewsBreak is a Content Intelligence platform that delivers hyper-local news and information to over 40 million monthly active users across the U.S. using advanced AI, recommendation systems, and adtech.
- **Entity Type**: Private (Series C, reached unicorn status in 2021)
- **Headquarters**: Mountain View, California, United States
- **Founded**: 2015
- **Founders**: Jeff Zheng (CEO)

## Core Business
- **Primary industry/industries**: Content Intelligence, Local News & Information, AI-Powered Recommendation Systems, Advertising Technology (Adtech)
- **Target customers**: B2C (consumers seeking local news), B2B (publishers, content creators, local businesses), and Enterprise (advertisers and agencies)
- **Mission or purpose statement**: Building the infrastructure layer for content intelligence, helping people live safer, more vibrant, and more truly connected lives by connecting and empowering local users, local content creators, and local businesses at scale.

## Products & Services
- **NewsBreak Platform**: A flagship mobile app and website that delivers personalized local news and information from over 10,000 sources to more than 40 million monthly active users across the U.S.
- **NBot**: An AI-powered agentic assistant that lets users personalize any digital engine (apps, platforms, websites) using natural language.
- **Publishing Platform (mp.newsbreakapp.com)**: B2B tools that help publishers, content creators, and local businesses engage audiences with monetization and audience-reach solutions.
- **Creator Program**: A platform for local content creators to distribute their work and monetize their audience.
- **Adtech & Monetization Solutions**: Targeted advertising solutions for local businesses, helping them connect with local audiences.

## Market Standing
- **Valuation/Market Cap**: Unicorn status (valuation over $1 billion) achieved in 2021. Latest valuation not publicly disclosed.
- **Total Funding**: $115 million in Series C funding led by Francisco Partners (2021). Total funding amount not fully disclosed.
- **Key Metric**: 40+ million monthly active users (MAU)
- **Notable Investors/Partners**: Francisco Partners (lead investor in Series C)
- **Growth Signals**: Reached unicorn status in 2021; recognized by Fast Company as #32 on the Top Workplaces for Innovators (2025); Great Place to Work® certified; growing workforce with active hiring across engineering, product, and business roles.

## Competitive Advantages
- **Content Intelligence Infrastructure**: A proprietary AI-powered platform that personalizes local news and information at scale, creating a unique data moat.
- **Hyper-Local Focus**: Serves over 10,000 local news sources, filling a critical gap in the declining local news market.
- **Large, Engaged User Base**: 40+ million MAU provides a strong network effect for both content creators and advertisers.
- **Advanced AI & Recommendation Systems**: Deep expertise in NLP, recommendation algorithms, and agentic AI (NBot) differentiates them from traditional news aggregators.
- **B2B & B2C Dual Model**: Generates revenue from both consumers (via engagement) and businesses (via advertising and publishing tools).

## Strategic Focus
- **Content Intelligence Leadership**: Doubling down on AI to build the "infrastructure layer" for content intelligence, enabling smarter connections between people, businesses, and information.
- **AI-Powered Innovation**: Continued development of agentic AI (NBot), LLM post-training, and AI-driven advertising agents to enhance personalization and monetization.
- **Local Market Dominance**: Expanding the network of local publishers, creators, and businesses to strengthen the hyper-local ecosystem.
- **Monetization Growth**: Scaling adtech and B2B tools to increase revenue from both SMBs and enterprise advertisers.

## Why Work Here
- **Culture of Innovation**: Recognized by Fast Company as one of the Best Workplaces for Innovators (2025), with a culture that values curiosity, autonomy, and collaboration. Employees work in decentralized, autonomous teams with real ownership over product areas.
- **High-Growth Environment**: A unicorn company on a high-growth trajectory, offering accelerated professional growth for those who "think big, move fast, and create real-world impact."
- **Great Place to Work® Certified**: 92% of employees are proud to be making a difference, 94% felt welcomed when they joined, and 84% say it's a great place to work (compared to 57% at a typical U.S. company).
- **Benefits**: Competitive healthcare benefits (flexible medical care, premium dental/vision), 401(k) matching, and a focus on mental, physical, and financial well-being.
- **Remote/Hybrid Policy**: HQ is in Mountain View, CA, with a presence in New York and Bellevue, WA. Job postings list specific locations, suggesting a hybrid or on-site model for most roles.
- **Engineering Culture**: Emphasis on ML, AI, recommendation systems, and adtech. Teams work with cutting-edge tech (LLMs, agentic AI, NLP) and are encouraged to pursue applied research, collaborate with academic institutions, and attend industry events.

## Sources
1. [NewsBreak Careers Page](https://careers.newsbreak.com/)
2. [NewsBreak Job Board (Greenhouse)](http://job-boards.greenhouse.io/newsbreak)
3. [NewsBreak LinkedIn](https://www.linkedin.com/company/newsbreak)
4. [PRNewswire - Fast Company Best Workplaces for Innovators 2025](https://www.prnewswire.com/news-releases/newsbreak-recognized-among-the-worlds-best-workplaces-for-innovators-by-fast-company-302552097.html)
5. [Great Place to Work - NewsBreak Profile](https://www.greatplacetowork.com/certified-company/7088585)

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