Senior Machine Learning Engineer

thorn; United States; Remote; USD 154,000 - 213,000; Full time

Job summary

thorn is seeking a senior machine learning engineer to build, deploy, and maintain production-grade models that surface exploited children faster and reduce online harm at scale. You will work in a distributed ML team within a larger product organization, collaborating with partners and cross-functional stakeholders.

You will own end-to-end model development from problem framing to deployment, monitor systems, and communicate results to both technical and non-technical audiences while advancing

Qualifications

• 5+ years of ML/AI experience with a master's or PhD in a quantitative discipline.
• Demonstrated ability to navigate ambiguous problems under legal and product constraints.
• Commitment to centering vulnerable users and online safety expertise.

Responsibilities

• Own end-to-end model development from problem formulation through deployment, monitoring, and ongoing maintenance.
• Identify data sourcing and labeling requirements, partnering with technical program management.
• Co-author labeling guides with domain experts and support labeling efforts.
• Review system design and code with ML engineers to uphold quality standards.
• Collaborate with product engineers on model serving infrastructure and deployment pipelines.
• Communicate problem framing, feature design, training choices, and evaluation results clearly to technical and non-technical audiences.
• Build external partnerships and present technical work at conferences and forums.
• Track emerging ML research and translate advances into applied safety solutions.

Skills

ML/AI experience 5+ years

Strong written communication

Remote-friendly collaboration

Python

PyTorch

TensorFlow/Keras

Hugging Face transformers

scikit-learn

OpenCV

FAISS or vector stores

ONNX/onnxruntime

AWS

Terraform

Kubernetes

CI/CD pipelines

Education

Master's or PhD in quantitative discipline

Tools

Python

PyTorch

TensorFlow/Keras

Hugging Face Transformers/Diffusers

scikit-learn

OpenCV

FAISS or similar vector stores

ONNX/onnxruntime

AWS

Terraform

Kubernetes

CI/CD pipelines

Job description

Role overview

A senior machine learning engineering role focused on building, deploying, and maintaining production-grade models, classifiers, and algorithms that help surface exploited children faster, remove abusive material at scale, and prevent harm before it spreads. The work happens within a small, distributed ML team embedded in a broader product and engineering organization, with close collaboration across external partners and cross-functional stakeholders.

Responsibilities

• Own end-to-end model development, from problem formulation through deployment, monitoring, and ongoing maintenance
• Identify data sourcing and labeling requirements, partnering with technical program management to keep priorities visible
• Co-author labeling guides with domain experts and support labeling efforts, which may include reviewing explicit but non-abusive content
• Review system design and code alongside other ML engineers to uphold team-wide quality standards
• Collaborate with product engineers on model serving infrastructure, deployment pipelines, and operational maintenance
• Communicate problem framing, feature design, training choices, and evaluation results clearly to both technical and non-technical audiences
• Build external partnerships and present technical work at conferences and community forums
• Track emerging ML research and translate promising advances into applied solutions for online safety challenges

Requirements

• 5+ years of experience in machine learning or artificial intelligence, supported by a master's or Ph.D. in a quantitative discipline
• Demonstrated persistence and technical depth navigating ambiguous problem spaces shaped by legal, product, and technical constraints
• Genuine commitment to centering vulnerable users and willingness to deepen expertise in online child safety and victim identification
• Comfort working with shifting requirements and collaborating across internal teams and external organizations
• Strong written communication skills suited to a highly distributed, remote-first team
• Collaborative mindset balancing product vision with engineering constraints, paired with empathy for users and teammates

Nice to have

• Hands-on experience with Python, PyTorch, TensorFlow/Keras, Hugging Face Transformers/Diffusers, scikit-learn/scipy, OpenCV, FAISS or similar vector stores, and ONNX/onnxruntime
• Familiarity with AWS, Terraform, Kubernetes, and CI/CD pipelines for model serving and infrastructure

Benefits and work setup

• Estimated compensation range of $154,000–$212,750 per year, with variation based on location, experience, and other factors
• Remote-first working model centered on home-based work, with periodic travel for company gatherings, team offsites, and conferences
• Broad benefits package and a stated commitment to an accessible, inclusive workplace, including reasonable accommodations for candidates and employees with disabilities