Cellular Data Science & Machine Learning Engineer Location: San Diego, California, United States Department: Hardware Summary Posted: May 16, 2025 Weekly Hours: 40 Role Number: 200604209 Are you passionate about invention and self-challenge? Do you thrive on pushing the limits of what’s considered feasible? Join our world-class modem team to craft sophisticated, innovative embedded firmware that delivers unprecedented performance. Collaborate across fields to transform hardware improvements into integrated designs, and help develop wireless systems technologies that continually outperform previous iterations. Work with cross-functional teams at Apple to push industry boundaries and enhance customer experiences worldwide. Description As a Data Science & Machine Learning Engineer, you will develop groundbreaking data processing pipelines based on machine learning models. You will demonstrate data science algorithms to analyze extensive data and logs efficiently, automatically addressing issues or providing recommendations. You will partner with firmware engineering teams to integrate and deploy ML models and data pipelines, supporting automation and debugging processes. Collaborate with a talented team to generate insights, develop models, and solve complex problems with meaningful impact. Minimum Qualifications Bachelor’s degree and at least 3 years of relevant industry experience Proficient Python developer with 3+ years of experience using ML tools like PyTorch, TensorFlow, HuggingFace Strong understanding of machine learning, deep learning, natural language processing, including LLMs, and ability to optimize models for various issues Hands-on experience implementing end-to-end machine learning projects Creative thinking with a focus on automation and reducing manual processes Preferred Qualifications Master’s or PhD degree Over 5 years of proven Python programming experience with ML tools Deep understanding of ML, DL, NLP, and LLMs, with experience optimizing models Experience developing ML and DL models, feature engineering, and deploying end-to-end solutions Ability to apply analytics and statistical methods to extract insights and actionable results Experience with relational (e.g., Postgres) and non-relational databases (e.g., MongoDB) Strong critical thinking and interpersonal skills, with a desire to learn new technologies #J-18808-Ljbffr Apple
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