Staff Machine Learning Engineer

This is a fully remote position, open to applicants in United States.

📋 Description

• Design, create, implement, test, and maintain machine learning systems, models, classifiers, algorithms, and pipelines.

• Act as a machine learning authority, offering expertise and support to legal, engineering, product, business development, and external affairs teams.

• Develop automated solutions to detect victims of child sexual abuse, facilitate the removal of abusive content, and prevent online exploitation.

• Ensure high standards of work quality and mentor fellow ML Engineers.

• Lead the design of machine learning systems, establish engineering standards, conduct technical meetings, and mentor engineering staff.

• Debug issues, perform code reviews, and support machine learning projects.

• Define strategies for data sourcing and labeling, and anticipate future data requirements.

• Create guidelines for data labeling and assist in labeling tasks, which may involve sexually explicit content.

• Identify dependencies between teams and assess technical risks; establish architectural guidelines and best practices for scalability and reliability.

• Represent Thorn at conferences and external engagements as a technical thought leader.

• Collaborate with engineers, product managers, product owners, and designers to outline requirements, scope, user needs, features, and deliverables.

• Maintain and deploy models, algorithms, and model-serving infrastructure.

• Enhance the innovation-to-impact cycle across products, academic collaborations, and external partnerships.

• Cultivate relationships and work collaboratively with external partners.

• Improve systems, create tools, and implement policies and patterns to boost team productivity.

• Communicate and document problem formulation, feature/model design, training, and evaluation outcomes to both technical and non-technical audiences.

• Discover new problem areas in online child safety and leverage relevant technological advancements.

• Lead the planning and upkeep of roadmaps in relation to feature-development cycles.

• Conduct data analysis as required.

• Collaborate with Product and Engineering teams during planning, software design, model development, and urgent customer support.

⛳️ Requirements

• A commitment to prioritizing the needs of the children Thorn serves.

• A willingness to learn about online child safety and victim identification.

• Over 8 years of experience in machine learning and/or artificial intelligence.

• More than 3 years of experience developing production-scale computer vision and/or NLP machine learning systems and pipelines.

• A Ph.D. or master’s degree in a quantitative field, or equivalent professional experience.

• A strong ability and desire to quickly learn and adopt new technologies.

• Capability to operate effectively in ambiguous situations with changing requirements.

• Experience working collaboratively with cross-functional internal and external stakeholders.

• A passion for machine learning and a knack for collaborative efforts.

• Empathy for team members and a strong advocacy for users.

• Ability to recognize unique opportunities and convert them into scalable solutions.

• Clear, efficient, and thoughtful communication; strong writing skills.

• Proficiency in AWS.

• Proficiency in Python.

• Experience with Pandas.

• Familiarity with PyTorch.

• Knowledge of scikit-learn/scipy.

• Experience with Terraform.

• Familiarity with CI/CD Pipelines.

• Proficiency in TensorFlow with Keras.

• Experience with Hugging Face Transformers/Diffusers.

• Familiarity with OpenCV.

• Knowledge of FAISS or other vector stores.

• Experience with ONNX/onnxruntime.

• Familiarity with Kubernetes.

🏝️ Benefits

• Remote-first work model, allowing employees to work from home most of the time.

• Company-wide gatherings.

• In-person team meetings and team-building events.

• Attendance at selected conferences.

• A comprehensive range of employee benefits (details available on the Thorn careers page).

• Reasonable accommodations for candidates and employees with disabilities.