Senior Machine Learning Engineer

DeepRec.ai; Sunnyvale (CA); On-site; USD 180,000 - 280,000; Full time

Job summary

DeepRec.ai in Sunnyvale, CA is seeking senior ML/CV engineers to push generative autonomy simulations using diffusion and video models. You will turn research into production-ready code and scale large models for deployment.

You will work on diffusion/video data generation conditioned on scenes, cameras, and trajectories, with emphasis on robust training and inference pipelines for real-world logs.

Qualifications

• 5+ years of building and shipping ML or computer vision systems.
• Hands-on experience with diffusion and video models (latent/video diffusion, DiTs).
• Experience training and fine-tuning large models.

Responsibilities

• Develop diffusion and video generation models for realistic sensor data.
• Condition generation on scene layout, camera pose, actors and trajectories.
• Ensure temporally consistent, multi-camera video generation.

Skills

5+ years ML/CV

Diffusion & video models

Large model training

Python & PyTorch

Production code

CUDA

Tools

Python

PyTorch

CUDA

Job description

I'm partnering with a well-funded autonomy and simulation company whose software is used by most of the world's major car manufacturers and by defence customers.

They turn real driving data into realistic simulation, and they're hiring senior engineers to push the generative side of the product using diffusion and video models.

What you'll work on:

• Diffusion and video generation models for realistic, controllable sensor data
• Generation conditioned on scene layout, camera pose, actors and trajectories
• Temporally consistent, multi-camera video
• Adding new scenarios, weather and lighting to real-world logs
• Combining generative models with 3D reconstruction
• Scaling training and inference of large models for production

What they're looking for:

• 5+ years building and shipping ML or computer vision systems
• Strong hands-on experience with diffusion and video models (latent/video diffusion, DiTs)
• Experience training and fine-tuning large models
• Python and PyTorch
• A track record of turning research into production code
• Bonus: 3DGS/NeRF, world models, multi-view consistent generation, distillation and efficient sampling, C++/CUDA, AV or robotics data, and publications at CVPR, NeurIPS, ICLR, ICML or similar.