About Pangram Labs

Pangram Labs’ mission is to protect authenticity by building the world’s best AI detection systems. We publish research on state-of-the-art AI detection techniques and algorithms, and build products to bring our technology into people's daily lives.

We are looking for high agency, mission-driven, and passionate builders to join our team. All roles are in person in Brooklyn, New York.

About the Team

We are a small, tight-knit team of researchers and engineers who care deeply about our work and each other. We believe that a small group of highly talented, empowered, and efficient people can outperform teams many times their size. Everyone on the team has meaningful ownership over the technical and strategic direction of the company.

Pangram is primarily an in-person company. We are high-touch, high-energy, and extremely collaborative by nature and choose to spend time together to do our best thinking and innovation.

About the Role

Pangram Labs is hiring a Computer Vision Engineer to build and ship the multimodal AI detection systems at the core of our product. You'll own models end to end — from data and training through deployment, serving, and monitoring in production — to build the most accurate AI detection software in the industry.

You'll train deep learning models that reliably identify AI-generated images, then take responsibility for getting them into production and keeping them performant, reliable, and continuously improving against an adversarial, fast-moving threat landscape. This is an engineering-first role: research is part of the work, but the job is measured by what ships and how well it runs at scale.

Responsibilities

• Train large-scale deep learning models to detect AI-generated content, and own the full lifecycle: data pipelines, training, evaluation, deployment, monitoring, and retraining

• Build and operate the production systems that serve detection models — inference services, batch pipelines, and the infrastructure behind them — with attention to latency, throughput, cost, and reliability

• Design evaluation and monitoring pipelines that catch model regressions and detect drift as new generative models emerge

• Build infrastructure for synthetic dataset creation and large-scale data processing

• Improve model accuracy, robustness, and efficiency through experimentation grounded in production metrics

• Work with engineering and product teams to translate models into shipped product features, and share results with technical and non-technical audiences through documentation, whitepapers, and blog posts

Requirements

• 3–5+ years of experience building and deploying ML systems in production, and/or a Ph.D. in AI, Machine Learning, Computer Vision, or a related area

• A strong engineering track record: shipping production code, deploying models, and building reliable systems. This can be demonstrated through significant contributions to AI products in industry, or through first-author publications at major AI/CV venues (CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, etc.)

• Experience training neural networks in PyTorch at scale, including distributed training

• Experience with AI infrastructure and distributed systems — model serving, pipelines, and the tooling required to run models in production

• Deep understanding of generative image models (diffusion models, GANs, autoregressive image models) and how they work

• Solid understanding of neural networks for video, audio, time series, and signal processing

• Familiarity with recent technical developments in LLMs

Nice to have

• Experience with MLOps tooling, CI/CD for ML, or model observability and monitoring at scale

• Experience or publications in image forensics or deepfake detection

• Experience with synthetic data, adversarial robustness, or interpretability

What we offer

• Salary Range: $230,000–$260,000 per year

• Competitive equity

• Healthcare benefits

• Free lunch at the office