Principal AI Scientist

Bark Technologies

2d•Remote

About The Position

At Bark, we’re on a mission to keep children safer online – both at home and at school. We use cutting-edge machine-learning technology to detect issues like cyberbullying, sexting, signs of depression, suicidal ideation, and more. We also offer internet filtering and screen time limits. Learn more at www.bark.us. The Principal AI Scientist is responsible for shaping Bark’s AI strategy and delivering high-impact, production-ready AI systems. Reporting to the CTO, this role provides technical leadership across Product & Engineering, translating advanced AI capabilities into reliable, responsible products.

Requirements

10+ years of experience in machine learning, applied AI, or data science, with a strong track record of shipping AI-powered products.
Familiarity with modern engineering environments, and AI tooling and infrastructure (e.g., PyTorch, TensorFlow, cloud-based ML platforms, MLOps).
Deep expertise in one or more relevant areas such as machine learning, generative AI, etc.
Strong experience building and maintaining systems, including data pipelines, training workflows, deployment, and monitoring.
Demonstrated ability to drive technical direction across multiple teams and initiatives.
Excellent communication skills and the ability to operate effectively in a mission-driven, cross-functional environment.

Responsibilities

Set technical direction for Bark’s AI systems in partnership with the CTO.
Drive improvements in model accuracy, robustness, explainability, and latency in real-world conditions.
Translate research and experimentation into durable product capabilities that integrate cleanly with Bark’s engineering stack.
Establish best practices for model lifecycle management, including training, evaluation, deployment, monitoring, and iteration.
Serve as a technical authority for AI/ML at Bark, influencing architecture, modeling approaches, evaluation standards, and system design across teams.
Influence product and technical decisions across teams through expertise.
Champion responsible AI practices, including fairness, privacy, transparency, and harm minimization.