Cellular Data Science & Machine Learning Engineer at Apple

San Diego, California, United States -

Full Time

Start Date

Immediate

Expiry Date

17 Feb, 26

Salary

0.0

Posted On

19 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Machine Learning, Python, PyTorch, Tensorflow, HuggingFace, Deep Learning, Natural Language Processing, LLMs, Reinforcement Learning, Fine Tuning, Feature Engineering, Analytics, Statistical Methods, SQL, Database Management

Industry

Computers and Electronics Manufacturing

Description

Do you have a passion for invention and self-challenge? Do you thrive on pushing the limits of what’s considered feasible? As part of a world class modem team, you’ll craft sophisticated leading-edge embedded firmware that deliver more performance in our products than ever before. You’ll work across disciplines to transform improved hardware elements into a single, integrated design. Join us, and you’ll help us innovate new wireless systems 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? As a Cellular 4G/5G Data Science & Machine Learning Engineer, you will be at the center of the embedded 5G/4G/multimode cellular system & firmware effort within a silicon design group responsible for designing and productizing state-of-the-art cellular SoCs. DESCRIPTION Data Science & Machine Learning Engineer will be responsible for developing state-of-the-art data processing pipeline based on machine learning models and leveraging data science algorithms to parse massive data and logs in timely manner to automatically solve the issues or provide recommendations for the next step of solving problem. In addition, you will be closely partnering with FW engineering teams in integrating and deploying ML models and data processing pipeline as part of entire automation system to deliver analysis results to benefit FW engineers in debugging issues. You will work with amazing team, brainstorm new ideas, and develop models and algorithms to solve complicated problems that have a substantial impact. MINIMUM QUALIFICATIONS Master’s degree in data science or computer science 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 Solid knowledge of reinforce-learning with experience in leveraging PPO/DPO/GRPO to enhance LLM model performance Ability to think creatively and identify, build, and support solutions and roadmaps focused on automation and reduction of manual processes PREFERRED QUALIFICATIONS Ph.D. degree in machine learning, data science or computer science 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 reinforce-learning with experience in leveraging 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 utilizing 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.Mango DB) 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

Responsibilities

The Cellular Data Science & Machine Learning Engineer will develop state-of-the-art data processing pipelines using machine learning models to analyze massive data and logs. This role involves collaborating with firmware engineering teams to integrate and deploy ML models for automation and debugging purposes.