SoC Machine Learning Software Engineer

at  Apple

SUMMARY

Posted: Oct 17, 2024
Role Number:200574250
By collaborating with other product development groups at Apple, you’ll push the industry boundaries of what wireless systems can do and improve the product experience for our customers worldwide. Join Apple’s world-class silicon development team as an ML SW Engineer on the Cellular FW team. As a key player, you will orchestrate the research, design, and implementation of groundbreaking AI/ML models, methodologies, and applications revolutionizing embedded 6G/5G/4G/multimode cellular firmware development and silicon/FW integration. In this role, you will be directly involved in our Cellular Modem firmware machine learning efforts, collaborating alongside our internal multi-functional teams and using your expertise in machine learning to improve device performance across diverse modem functions. Additionally, you will demonstrate your knowledge and hands-on experience to apply Gen AI and LLMs to improve engineering development workflow automation and efficiency. Your work will impact every Apple product, pushing the industry boundaries of what wireless systems can achieve with 6G and beyond!

DESCRIPTION

As an ML SW Engineer, you will be at the forefront of using AI/ML to transform cellular firmware development. Your responsibilities will include: - Develop and deploy innovative ML models on Apple Silicons, focusing on Cellular Modem algorithms and usage scenarios. - Research, evaluate, design, and implement deep learning and Gen AI architectures to enhance inherent model performance. Apply these architectures to cellular modem firmware development and HW/SW system bring-up applications. - Work closely with multi-functional teams across Apple to drive innovation and improve the product experience for our customers worldwide.

• Minimum BS with 3+ years of proven experience.
• Hands-on experience in building, training, and deploying deep learning models, including LSTM, CNN, RNN, transformers.
• Have practical experience and knowledge of applying ML/AI methods to real-world data analysis and usage scenarios, using generative AI and modern machine learning methods, particularly deep neural networks and reinforcement learning.
• Proven knowledge of software engineering principles and core computer science fundamentals and excellent proficiency in Python and C/C++.
• Knowledgeable in building architectures and incorporating SOTA LLMs into application frameworks.
• Experience in building Gen AI applications to tackle real-world engineering problems, demonstrating techniques like RAG, Prompt engineering, and Fine-tunings.
• Familiarity with toolchains and packages like PyTorch, Langchain, CoreML, MLX.

PREFERRED QUALIFICATIONS

• MS or Ph.D.
• Experience with relational database (e.g Postgres), SQL, non-relational database (e.g.Mango DB) and vector DBs.
• Experience in using various analytics and statistical methods for feature extraction and abstraction, to transform data into useful insights and actionable results.
• Top-notch abilities to conduct independent research, prototype, evaluate, and complete end-to-end design iterations.
• Embedded and HW/SW integration experience.

• Minimum BS with 3+ years of proven experience.
• Hands-on experience in building, training, and deploying deep learning models, including LSTM, CNN, RNN, transformers.
• Have practical experience and knowledge of applying ML/AI methods to real-world data analysis and usage scenarios, using generative AI and modern machine learning methods, particularly deep neural networks and reinforcement learning.
• Proven knowledge of software engineering principles and core computer science fundamentals and excellent proficiency in Python and C/C++.
• Knowledgeable in building architectures and incorporating SOTA LLMs into application frameworks.
• Experience in building Gen AI applications to tackle real-world engineering problems, demonstrating techniques like RAG, Prompt engineering, and Fine-tunings.
• Familiarity with toolchains and packages like PyTorch, Langchain, CoreML, MLX