Staff Machine Learning Engineer

About the Role

As a Staff ML Engineer at Thorn, this role will design, build, deploy and maintain world class models, classifiers and algorithms to increase Thorn’s capabilities to achieve our mission of the elimination of child sexual exploitation. They will be the go-to expert in one or more domains of machine learning and provide critical guidance to multiple teams across legal, engineering, product, business development and external affairs. They will directly contribute to the Machine Learning team’s critical function in Thorn’s mission - building automated solutions that:

1. Reduce the time it takes to identify a child sexual abuse victim, elevating the most vulnerable and high risk victims from an ocean of online content
2. Enable the removal of child sexual abuse material from the internet, finding known and new content
3. Prevent online abuse from happening in the first place, detecting abusive content before it spreads

They are responsible for ensuring that their work is high quality, as well as mentoring other ML Engineers. They will thrive in highly ambiguous problem spaces and be able to creatively design and build scalable solutions with minimum direction. They will demonstrate persistence and strong technical expertise to navigate legal, product, and technical constraints. They are responsible for partnering with the engineers, product manager and designers across different products to drive requirements, as well as any and all relevant external partners, taking into account all stakeholder needs.

What You’ll Do

• Own end-to-end model development: design, build, test and maintain machine learning systems and algorithms
• Lead machine learning system designs, set engineering standards, lead technical meetings and proactively engage and mentor other engineers
• Help debug, do code review, and support general machine learning initiatives led by other members of the Machine Learning team.
• Define data sourcing and labeling strategy for your technical domain, proactively identifying future data needs and partnering with the Sr. Technical Program Manager to drive planning and prioritization
• Work closely with specialists at Thorn to create data labeling guides and support labeling efforts. This may involve engaging with sexually explicit material that is not child sexual abuse material
• Look for opportunities to streamline and reuse work, proactively identifying cross-team dependencies. Anticipate technical risks across ML systems, define architectural guardrails, establish best practices for scalability and reliability
• Represent Thorn as a technical thought leader at conferences and other external forums, advancing the field and strengthening strategic partnerships
• Collaborate with engineers, product managers, product owners, and designers to drive requirements, define scope of work, engage with users, and translate user needs into features and deliverables
• Collaborate with engineers on product teams to maintain and deploy models, algorithms and model serving infrastructure
• Look for opportunities, in collaboration with the Sr. Technical Program Manager, to improve the innovation -> impact cycle across product, academic collaborations, and other external partnerships
• Build relationships and collaborate with external partners
• Look for opportunities to improve systems, author tools and introduce policies/patterns that raise productivity for the Machine Learning team
• Clearly communicate and document problem formulation, feature/model design, training, and evaluation results to technical and non-technical audiences
• Identify new problem spaces within online child safety. Stay abreast of technical developments and breakthroughs with an eye towards applying solutions to our issue space.
• Drive roadmap planning and cadence of maintenance vs. new feature development for your areas of ownership
• Conduct data analysis as needed to improve cross-functional understanding
• Collaborate closely with Product and Engineering during planning, software design, model development, and time-sensitive customer support efforts.

What We’re Looking For

• You have a commitment to putting the children we serve at the center of everything you do
• You have a willingness to learn about online child safety and victim identification.
• You have 8+ years background in machine learning and/or artificial intelligence, with 3+ years experience in building production-scale computer vision and/or NLP machine learning systems and pipelines
• You have a Ph.D or master’s degree in a quantitative field, or equivalent professional experience.
• You have an ability and interest in learning and adopting new technologies quickly
• You can work with ambiguity, shifting requirements and collaborate with cross-functional internal and external stakeholders
• You have a passion for machine learning and an aptitude to work in a collaborative environment, can demonstrate empathy for our team and strong advocacy for our users, while balancing the vision and technical constraints of engineering. Success on this team requires humility, curiosity, and a willingness to both teach and learn.
• You excel at identifying unique opportunities and translating them into scalable solutions that align cross-functional stakeholders around a clear, compelling, and actionable vision
• You communicate clearly, efficiently, and thoughtfully. We’re a highly-distributed team, so written communication is crucial

Technologies We Use (for relevant roles)

• AWS
• Python
• Pandas
• PyTorch
• scikit-learn/scipy
• Terraform
• CI/CD Pipelines
• Tensorflow with Keras
• Hugging Face Transformers/Diffusers
• OpenCV
• FAISS or other vector stores
• ONNX/onnxruntime
• Kubernetes

Compensation and Benefits

A reasonable estimate of the compensation range for this role is $171,000-$235,750/year. This range takes into account the wide range of factors that are considered in making compensation decisions, including but not limited to location; skill sets; experience and training; licensure, and certifications.

Our remote-first work model is structured around working from home most of the time. But, there will be times that employees are expected to travel. For example, Thorn may host company-wide gatherings, and smaller teams may hold in-person meetings and team-building events, or require attendance at specific conferences.

At Thorn, we know that great people make a great organization. We value our people and offer employees a broad range of benefits. Learn more about what working at Thorn can mean for you.