Job Description

Machine Learning / Computer Vision Engineer - Generative AI

Sunnyvale, California, United States | Machine Learning and AI

Description

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 infrastructure (e.g., AWS, GCP). Research foundation models, multimodal AI, and reinforcement learning to enhance generative capabilities. Collaborate with data engineers to preprocess datasets, create synthetic data, and optimize data pipelines. Deploy models into production using ML frameworks (TensorFlow, PyTorch) and MLOps best practices. Optimize inference for latency and efficiency through quantization, pruning, and edge deployment. Stay updated with AI research, contribute to patents/publications, and participate in open-source projects. Work with product teams to integrate AI into applications like content creation, automation, and digital assistants.

Minimum Qualifications

• BS degree and at least 3 years of relevant industry experience.
• Experience with computer graphics fundamentals (3D Gaussian splats, path tracing, rendering).
• Familiarity with real-time/path tracing renderers (VRay, Arnold, Unreal Engine).

Preferred Qualifications

• Experience with RLHF (Reinforcement Learning with Human Feedback).
• Contributions to open-source ML projects or publications in top AI conferences.
• Experience in automated content generation, synthetic media, or AI-powered creative tools.
• Over 5 years of hands-on experience in Machine Learning & Deep Learning.
• Expertise in Generative AI models (Diffusion Models, GANs, VAEs, Transformers).
• Experience using synthetic data for training computer vision models.
• Proficiency in Python and ML frameworks like TensorFlow, PyTorch, JAX.
• Experience with NLP, Computer Vision, or Multimodal AI.
• Familiarity with LLMs (GPT, LLaMA, Mistral) and fine-tuning techniques like LoRA, PEFT.
• Experience deploying models with Docker, TensorRT, ONNX.
• Strong knowledge of cloud computing (AWS, GCP) and distributed training.
• Experience with MLOps, model versioning, and monitoring tools (MLflow, Weights & Biases).
• Strong problem-solving skills and ability to work in a fast-paced environment.

Note: The salary range for this role is $147,400 to $272,100, depending on skills and experience. Apple offers comprehensive benefits, stock programs, and opportunities for career growth. This role may also be eligible for bonuses, relocation, and educational reimbursements.

Apple is an equal opportunity employer committed to diversity and inclusion. We promote equal opportunity regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other protected characteristics.

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