Apple's Synthetic Data Group (SDG) is seeking a Machine Learning Engineer with expertise in Generative AI to design, train, and deploy advanced generative models for applications across text, image, and video domains, aiming to push the boundaries of creativity and automation.
Requirements
- Experience in Computer Graphics fundamentals (3D Gaussian Splats, path tracing, rendering, ...)
- Familiarity with real time / path tracing renderers (VRay, Arnold, Unreal Engine, ...).
- Experience with RLHF (Reinforcement Learning with Human Feedback).
- Strong expertise in Generative AI models (Diffusion Models, GANs, VAEs, Transformers).
- Proficiency in Python and ML frameworks like TensorFlow, PyTorch, JAX.
- Experience with NLP, Computer Vision, or Multimodal AI.
- Familiarity with LLMs (GPT, LLaMA, Mistral, etc.) and fine-tuning techniques like LoRA, PEFT.
Responsibilities
- Design, train, and fine-tune Generative AI models (e.g., GANs, VAEs, Diffusion Models, Transformers like GPT, Stable Diffusion).
- Develop and optimize large-scale deep learning models for text, image and video generation.
- Implement efficient training pipelines using distributed computing and cloud-based infrastructure (e.g., AWS, GCP).
- Research and experiment with foundation models, multimodal AI, and reinforcement learning to enhance generative capabilities.
- Collaborate with synthetic data engineers to preprocess datasets, create synthetic data, and optimize data pipelines.
- Deploy generative AI models into production using ML frameworks (TensorFlow, PyTorch) and MLOps best practices.
- Optimize model inference for latency and efficiency, leveraging quantization, pruning, and edge deployment strategies.
Other
- BS and a minimum of 3 years relevant industry experience.
- Contributions to open-source ML projects or publications in top AI conferences.
- Experience in automated content generation, synthetic media, or AI-powered creative tools.
- 5+ years of hands-on experience in Machine Learning & Deep Learning.
- Strong problem-solving skills and ability to work in a fast-paced, product-focussed environment.
