Senior Machine Learning Engineer

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