Machine Learning Engineer (Applied AI)
We are looking for an experienced Machine Learning Engineer to help us extract value from manufacturing data and apply the AI/ML technologies (e.g. classification, regression via structured data and image data) into the real-world production. You will lead all the processes from requirement analysis, data collection, cleaning, and preprocessing, to training models and deploying them to production.
As a Machine Learning Engineer, you will have the opportunity to work with all the line of business to enable the mass creation of impossible Apple products that people know and love on this planet. If you're excited about making AI technology more impactful to the factories, this role is your chance to make a significant mark. In this role you will:
- Collaborate with business teams to analyze key business problems and develop innovative ML solutions
- Design advanced machine learning models that solve real-world problems and validate ML solutions end-to-end
- Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready
- Monitor and maintain deployed models to ensure they continue delivering value
- Connect with other AI/ML teams within Apple and be a trusted advisor for the ML knowledge and experience
- 6+ years of experience in applying machine learning technologies to solve real-world business problems
- Demonstrated experience in requirement analysis, can transform business problems into ML solutions very well, can communicate with both technical and non-technical stakeholders clearly
- Experienced in building, deploying and running Machine Learning applications or services
- Demonstrated expertise in machine learning, deep learning, or reinforcement learning
- Proficiency in implementing data-intensive pipelines and applications using programming languages such as Python, Java or Golang
- Strong written and verbal communication skills
- Bachelor or above in Computer Science, Machine Learning, Data Science, Statistics, Operations Research, Mathematics, or a related field
- Practical experience in at least one of the following domains: time series forecasting, anomaly detection, search and recommendation systems, feedback control, interpretable machine learning or computer vision
- Hands-on experience working with deep learning toolkits such as Scikit-Learn, AutoGluon, PyTorch or TensorFlow
- Strong foundation in data structures, algorithms, and software engineering principles.
- Experience with SQL and database systems such as PostgreSQL
- Experience with building ETL pipeline in data warehouse such as Snowflake
- Experience working on Linux and macOS based platforms