As a Machine Learning Engineer for Magic Leap’s Lifestream teamyou 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.