Machine Learning Engineer

Magic Leap   •  

Plantation, FL

Industry: Retail & Consumer Goods

  •  

Less than 5 years

Posted 66 days ago

This job is no longer available.

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

Key Responsibilities:

  • 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

Basic Qualifications:

  • 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

Preferred Skills:

  • 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

Education:

  • Master's Degree in a technical discipline or equivalent experience

Additional Information

All your information will be kept confidential according to Equal Employment Opportunities guidelines.