Cellular Data Science

2 weeks ago

San Diego, California, United States Apple Full time
Do you have a passion for invention and self-challenge? Do you thrive with pushing the limits of what's considered feasible? As part of a best-in-class modem team, you'll craft sophisticated, innovative embedded firmware that delivers more performance in our products than ever before. You'll work across teams to transform improved hardware elements into a single, integrated design.

Join us, and you'll help us innovate new wireless system technologies that continually outperform the previous iterations By collaborating with other product development groups across Apple, you'll push the industry boundaries of what wireless systems can do and improve the product experience for our customers across the world Do you want to have an impact on every single Apple product?

Description
As a Cellular 4G/5G Firmware Data Science & Machine Learning Engineer, you will be at the center of the embedded 5G/4G/multimode cellular firmware effort within a silicon design group responsible for designing and productizing pioneering cellular SoCs.

Minimum Qualifications
Minimum requirement of a bachelors degree.

Proficient Python developer with proven programming skills using standard ML tools such as PyTorch, Tensorflow, HuggingFace, etc.

Good understanding of machine learning, deep learning and natural language (including LLMs) processing and ability to optimize machine learning models to adapt to solving various kinds of issues.

Experience in fine tuning LLM model with SFT, LoRA and other techniques.

Proven knowledge of reinforcement learning with experience in employing PPO/DPO/GRPO to enhance LLM model performance.

Ability to think creatively and identify, build, and support solutions and roadmaps focused on automation and the reduction of manual processes.

Preferred Qualifications
MS or Ph.D. degree in machine learning, data science or computer science is preffered.

Proficient Python developer with 5+ years proven programming skills using standard ML tools such as PyTorch, Tensorflow, HuggingFace, etc.

Solid understanding of machine learning, deep learning and natural language (including LLMs) processing and ability to optimize machine learning models to adapt to solving various kinds of issues.

Have a deep understanding of reinforcement learning with experience in employing PPO/DPO/GRPO to enhance LLM model performance.

Experience in fine tuning LLM model with SFT, LoRA and other techniques.

Experience in developing machine learning models and /or deep learning models, feature engineering, and rich experience in implementing end-to-end machine learning projects.

Experience in applying analytics and statistical methods to transform data into useful insights and actionable results.

Experience with relational database (e.g Postgres), SQL and non-relational database (e.g. MongoDB).

Ability to think creatively and identify, build, and support solutions and roadmaps focused on automation and reduction of manual processes.

Strong critical thinking and communication skills with the ability and desire to learn and evaluate new technologies.

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