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Senior Machine Learning Engineer

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Onsite

Senior Machine Learning Engineer

NewsBreak

Senior Machine Learning Engineer

Skills

PythonJavaPyTorchTensorFlowMachine LearningAIScala

2 months ago

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Important information


Salary:

$195,000 – $230,000 / year

Location:

San Francisco, CA, USA

Work mode:

Onsite

Published on:

12 August 2026

What they need


Who you are

  • 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

What the job involves

  • 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
  • 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
  • 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
  • Embrace AI-assisted development workflows, including LLM-powered coding, debugging, and analysis
  • Apply AI across feature ideation, prototyping, and experiment analysis
  • Contribute to 0–1 AI-powered projects, helping take ideas from early exploration to MVP and production

Benefits

  • Work from home opportunities
  • 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 benefit programs
  • Team activity budget

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