As a Machine Learning Engineer for Magic Leap's Lifestream team you will have responsibility for the planning and development of our machine learning function / framework in support of the implementation of our Lifestream business function and how it integrates within our product portfolio.
You will be responsible for:
- Build machine-learning models using deep learning techniques for computer vision tasks such as sematic segmentation, object detection, video understanding, etc.
- Address large scale challenges in the machine learning development cycle, especially around distributed training in the cloud and data engineering
- Manipulate high-volume, high-dimensionality, structured data from driving logs for training and testing deep networks
- Work closely with Data Engineers and Data Scientists to create analytical variables, metrics, and models
- Work closely with data scientist to solve difficult engineering and machine learning problems and produce high- quality code
- Choose and use the right analytical libraries, programming languages & framework for each task
- Develop your abilities and understanding of data science methodologies and approaches
- Refactor code into reusable libraries, APIs, and tools
- Minimum of 3 years of professional software engineering experience, including testing and deploying iterative releases of software systems
- Minimum of 1 year of experience applying implementing, and/or developing machine learning or statistical algorithms
- Proficiency in C# and/ or C++ and SQL
- Experience with large- scale data processing and analysis
- Advance knowledge of unstructured data and machine learning technologies
- Good understanding of machine learning fundamentals, including measures of accuracy, common linear and non-linear algorithms , bias and variance and performance considerations
- Experience building production systems based on Machine Learning lifecycle
- Familiarity with statistical language modeling
- Experience in cybersecurity Excellent communication skills, high attention to detail and proven ability to use metrics to drive decisions
- Master's Degree in a technical discipline or equivalent experience
All your information will be kept confidential according to Equal Employment Opportunities guidelines.