Role Description

We are looking for a talented AI Research Engineer to join our computer vision research team. In this role, you will work closely with our research team, implementing, training, and evaluating state-of-the-art image and video generation models. You will own the engineering execution that turns research ideas into working systems:

• Building robust data pipelines
• Running and stabilizing large-scale training
• Implementing models from papers
• Optimizing for speed/efficiency
• Running rigorous evaluations

This is a high-impact implementation and execution role. This role is ideal for engineers who enjoy building reliable ML systems and scaling research ideas into production-quality training pipelines. The ideal candidate is someone who gets deep satisfaction from:

• Making complex systems work
• Translating research ideas into reliable, scalable code
• Debugging training instabilities
• Delivering measurable improvements in training stability, model quality, and inference efficiency

This is an excellent opportunity to work closely with experienced researchers, gain deep hands-on exposure to cutting-edge model training techniques, latest research methods in diffusion/transformer-based generation, large-scale experimentation, and efficiency innovations, all while contributing directly to production-grade models.

Qualifications

• 2–5 years of hands-on experience building and training ML systems, with strong ownership of results
• Fluency in PyTorch: comfortable reading, writing, and debugging both training and inference code
• Experience training or fine-tuning generative models (diffusion models, transformers, VAEs, or similar) from scratch or near-scratch
• Solid understanding of distributed training workflows and practical debugging of large training runs
• Demonstrated ability to read and implement AI research papers in computer vision
• Familiarity with cutting-edge computer vision models and research literature in the image and video domain
• Experience building data pipelines for large-scale image or video datasets
• Strong debugging skills: comfortable diagnosing both engineering bugs and training failures
• Strong engineering mindset: writing clean, reliable, debuggable code; profiling tools; handling numerical issues at scale

Requirements

• Build and maintain end-to-end data pipelines for large-scale image and video datasets: collection, filtering, augmentation, conditioning alignment, and efficient storage/sampling
• Implement model architectures (diffusion, autoregressive, flow-based, diffusion transformers, etc.) and maintain high-throughput PyTorch training loops for large-scale image and video diffusion models
• Run and manage large-scale training experiments on multi-GPU and multi-node setups (DDP, FSDP, DeepSpeed)
• Debug training instabilities, loss spikes, and convergence issues
• Apply quantization, pruning, and knowledge distillation techniques to compress models without sacrificing quality
• Collaborate with researchers and translate state-of-the-art research papers into working implementations in our internal codebase (e.g., new attention mechanisms, sampling schedules, or conditioning methods)
• Build and maintain evaluation pipelines of image quality, video consistency, and perceptual metrics
• Set up and maintain human annotation and evaluation pipelines using services like AWS GroundTruth
• Profile and optimize training speed, GPU memory utilization, and iteration time
• Implement inference optimizations to reduce latency and compute cost
• Work with acceleration toolchains such as torch.compile, Triton, TensorRT, or ONNX where appropriate

Benefits

• Competitive salary and generous company equity
• Medical, dental, and vision insurance – 99.99% of premiums covered by Cantina
• 42 days of paid time off, including:
• 15 PTO days
• 10 sick days
• 15 company holidays
• 2 floating holidays
• Generous parental leave & fertility support
• 401(k) retirement savings plan
• Lifestyle spending account – $500/month to use however you’d like
• Complimentary lunch and snacks for in-office employees
• One Medical membership, and more!