About the RolePangram 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
