Posted: May 6, 2020
Role Number: 200169370
Apple is looking for ML/Deep Learning engineers to develop and integrate machine learning technologies for autonomous systems. You will work on a hardware/software product enabled by the ML technologies you build.
- Develop features and models to improve the capabilities of large-scale Deep Learning-based systems.
- Scale up models, build training datasets and tune parameters to maximize system performance.
- Build software that improves your rate of experimentation and helps you make better decisions about what to try next.
- Work with the team to deploy models in a mission critical environment.
- Able to train and debug deep learning systems: Defining metrics and datasets, performing error analysis, training models in a modern DL framework (such as TensorFlow, PyTorch, Keras, etc.)
- Familiar with current DL literature and the math of machine learning: optimization methods, common types of models and layers, etc.
- Strong background in Python development with Linux. You write clean, correct code while iterating on experiments in Python. Ability to understand and contribute to C++-based software is a plus.
- Excellent communication skills. You collaborate effectively with other teams and communicate clearly about your work.
Working with the team you'll join a fantastic team of hardworking engineers and researchers with deep experience in robotics, machine learning, and software engineering. We hope you're excited about the values that drive us: - Passion for the mission: We're here to make something great. We take on whatever work is right for the product and strive for the best possible results. - Modesty: The right answer is more important than being right. We search for solutions as a team and value clear-eyed feedback. - Lean habits: You can't grow without limits. Time constraints and big goals inspire us to sharpen our focus and learn to make great decisions.
Education & Experience
Bachelors, Masters, or PhD Degree in Computer Science/Machine Learning or equivalent professional experience.