Staff Machine Learning Engineer

Role overview

Staff Machine Learning Engineer designing, deploying, and maintaining models, classifiers, and algorithms used to combat online child sexual exploitation. The role combines deep hands-on machine-learning work with technical leadership, mentoring, data strategy, cross-functional product development, and collaboration with external partners. Success requires working thoughtfully in ambiguous, sensitive problem spaces while balancing legal, ethical, user, and engineering constraints.

Responsibilities

- Own the full model lifecycle, from system design and data preparation through development, testing, deployment, maintenance, and improvement. - Lead machine-learning architecture and engineering standards, facilitate technical discussions, review code, debug systems, and mentor other engineers. - Define data-sourcing and labeling strategies, identify future data needs, and create practical labeling guidance with subject-matter specialists. - Partner with engineers, product managers, product owners, designers, and users to shape requirements, scope work, and translate needs into deliverables. - Work with product engineering teams to deploy models, algorithms, and model-serving infrastructure reliably. - Identify reusable solutions, cross-team dependencies, technical risks, scalability improvements, and architectural guardrails. - Represent the organization in technical forums and build productive relationships with academic, nonprofit, law-enforcement, and other external partners.

Requirements

- Strong professional experience building and operating machine-learning systems and algorithms end to end. - Expertise in one or more machine-learning domains, with the judgment to choose approaches that are accurate, scalable, maintainable, and appropriate to the problem. - Ability to work independently in ambiguous environments and navigate legal, product, technical, and stakeholder constraints. - Demonstrated technical leadership, mentoring ability, and experience setting engineering or ML standards. - Clear, concise written and verbal communication, especially in a highly distributed team. - Empathy for users and colleagues, plus the humility, curiosity, persistence, and willingness to teach and learn needed for sensitive mission-driven work.

Nice to have

- Experience with AWS, Python, Pandas, PyTorch, scikit-learn, SciPy, TensorFlow/Keras, Hugging Face, OpenCV, vector stores, ONNX, Kubernetes, Terraform, or CI/CD pipelines. - Experience with computer vision, information retrieval, model serving, or large-scale content classification. - Comfort engaging with sexually explicit material that is not child sexual abuse material as part of labeling or evaluation work.

Benefits and work setup

The estimated compensation range is $171,000–$235,750 per year, depending on factors such as location, skills, experience, training, licensure, and certifications. The role is remote-first and primarily home-based, with occasional travel for organization-wide gatherings, team meetings, team-building events, or conferences. The source describes a broad benefits package and an inclusive workplace with reasonable accommodations.