# Senior Machine Learning Engineer, Trust

**Company:** [Airbnb](https://hotfix.jobs/companies/airbnb)
**Location:** Remote
**Role:** ML Engineering
**Salary:** $200k – $235k/yr
**Experience:** 5+ years
**Skills:** Python, Scala, Java, TensorFlow, PyTorch, LLMs, Generative AI, AI Agents, Machine Learning, feature engineering, Transformers, Deep Learning, Data Engineering, A/B Testing, multimodal models
**Posted:** 2026-08-14

> Builds and productionizes machine learning systems for trust and safety, including abuse detection, autonomous AI agents, and evaluation frameworks. The role requires 5+ years of applied ML experience, strong Python skills, experience with LLMs and scalable pipelines, and a relevant advanced degree or equivalent background.

## Job Description

## Responsibilities
- Frame and prototype machine learning and agentic solutions for ambiguous trust and safety problems.
- Design, build, and productionize end-to-end machine learning pipelines for batch and real-time use cases, including feature engineering, model training, evaluation, and deployment.
- Build and improve abuse behavior detection across multiple defenses.
- Design, launch, and iterate on AI agents that automate trust decisions, including orchestration, tool interfaces, and quality guardrails.
- Build benchmarks, evaluation harnesses, and instrumentation to measure agentic and model decision quality.
- Develop specialized trust and safety models and use LLMs and AI agents to accelerate model development.
- Write, review, and ship clean, testable code while improving model pipelines and scalability.
- Work with large-scale structured and unstructured data to continuously improve machine learning models.
- Partner with front-line defense teams to validate solutions through experiments and holdouts and quantify business and operational impact.
- Participate in code reviews, design discussions, and cross-team collaboration.

## Requirements
- 5–10 years of industry experience in applied machine learning, with a track record of building and productionizing models at scale.
- 1–2+ years of hands-on experience with LLMs and generative AI, including agentic frameworks, orchestration, and evaluation.
- Strong Python programming skills and familiarity with Scala, Java, or equivalent.
- Understanding of machine learning best practices, including training/serving skew minimization, A/B testing, feature engineering, and model selection.
- Knowledge of gradient-boosted trees, neural networks, transformers, and deep learning.
- Experience with TensorFlow, PyTorch, or equivalent machine learning frameworks.
- Experience with data engineering and end-to-end machine learning pipelines, including batch and real-time systems.
- Experience designing evaluation methodologies for machine learning or LLM systems, including benchmarks, ground truth, offline and online metrics, and calibration.
- Exposure to architectures for large-scale software applications, well-designed APIs, high-volume data pipelines, and efficient algorithms.
- Experience with test-driven development, incremental delivery, and deployment practices.
- Bachelor's, master's, or PhD in computer science, machine learning, or a related field.

## Nice-to-haves
- Experience with multimodal models, including vision, document, or speech models.
- Exposure to trust and risk domains such as fraud detection, anomaly detection, identity, or account integrity.

## Compensation and Benefits
- Base pay range: **$200,000–$235,000 USD**.
- May also be eligible for bonus, equity, benefits, and Employee Travel Credits.

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