Senior AI Accessibility Engineer

Deque is seeking a highly experienced Senior AI Engineer to drive the next generation of intelligent, accessible technology. In this role, you will take ownership of designing, deploying, and scaling advanced AI and machine learning systems that power automated accessibility testing, intelligent analysis of scan results, and new product capabilities that advance Deque’s mission of digital equality.

As a senior technical leader, you will architect solutions that are robust, ethical, and production-ready, ensuring seamless integration into Deque’s core product suite. You will also help shape technical strategy, mentor peers, and set engineering best practices for ML deployment at scale

• Lead the design, training, and deployment of ML models in production environments with millions of users.
• Apply cutting-edge methods across computer vision, NLP, supervised/unsupervised learning, and representation learning to accessibility problems.
• Own the full ML lifecycle: from data collection and labeling strategy, to model evaluation and monitoring, to continuous improvement in production.
• Drive engineering excellence through expert-level Python development, ensuring codebases are clean, scalable, and maintainable.
• Champion responsible and ethical AI practices, with a focus on transparency, fairness, and accessibility impact.
• Collaborate cross-functionally with product managers, designers, and accessibility experts to identify high-impact opportunities.
• Apply state of the art methods to advance the field of accessibility.

• 5+ years of experience and a proven track record in machine learning or AI engineering, with a strong focus on deploying models in production environments.
• Expert with Python development (5+ years), and experience with common ML libraries such as TensorFlow, PyTorch, Scikit-learn, or Hugging Face Transformers.
• Experience building and maintaining scalable ML infrastructure
• Strong back-end engineering skills, including designing APIs, integrating with cloud services, and building infrastructure to support ML workflows.
• Hands-on experience with data engineering tools and workflows (e.g., AWS Glue, Athena, Spark, or similar).
• Strong understanding of model lifecycle management, including training, evaluation, deployment, and monitoring in real-world systems.
• Familiarity with web technologies (HTML, CSS, JavaScript) and an interest in digital accessibility.
• Excellent communication skills, with the ability to explain complex ML concepts to both technical and non-technical audiences.

• Computer Vision, NLP
• Docker & AWS
• Accessibility knowledge