Business Segment: Digital Predix Products & Technology
Location(s): United States; California; San Francisco
About Us: At GE Digital, we are creating technology and solutions to enable social, mobile, analytical and cloud capabilities for the Industrial Internet. The Industrial Internet is an open, global network that connects people, data and machines. It’s about making infrastructure more intelligent and advancing the industries critical to the world we live in. At GE, we believe it’s about the future of industry—energy, healthcare, transportation, manufacturing. It’s about making the world work better.
We are a well-resourced, rapidly growing team inside of GE Digital whose charter is to build machine learning powered applications on top of GE’s treasure trove of data assets. Our current team built a successful start-up business by putting sophisticated ML systems into production at scale. Now we are leveraging our ML application platform to drive massive value in a range of data-driven use cases across the various GE business units. Wise's application framework combines the latest virtualization and distributed systems solutions with leading web and visualization technologies in order to provide production-ready machine-learning insights to the enterprise.
GE offers a great work environment, professional development, challenging careers, and competitive compensation. GE is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other characteristics protected by law.
Role Summary: The Machine Learning technology at GE/Wise places strong emphasis on combining both the latest advances in machine learning, computer architecture, and high performance algorithms. The bedrock of our core technology is usually implemented in C++ for efficiency, and it may use specialized hardware.
A successful applicant is expected to use their extensive implementation expertise to engineer highly efficient, scalable, and novel machine learning software for the company’s core technology stack. The engineer will spearhead the adaptation of algorithms developed at a research stage into production-grade implementations as well as collaborating with researchers on the development of new algorithms. This position may include development on embedded and programmable processors as well as fast implementations of computer vision, natural language processing, deep learning, graphical, physics-based models, and time-series algorithms.
Pursuing an MS or PhD in Computer Science or Computer Engineering. Exceptional candidates with degrees in other disciplines will be considered
Legal authorization to work in the U.S. is required. GE may agree to sponsor an individual for an employment visa now or in the future if there is a shortage of individuals with particular skills.
Must be willing to work out of an office located in San Francisco, CA
Any offer of employment is conditioned upon the successful completion of a background investigation and drug screen
Pursuant to the Los Angeles/San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records
Advanced C++ knowledge including intimate familiarity with the C++11 and C++14 standards, template meta-programming, and policy-based design.
Advanced ML knowledge without this will be considered a non-starter.
Proficient in Python, Pandas, NumPy, and ability to wrap complicated C++ codes in Python.
Experience with machine learning, computer vision, and statistics (including deep learning algorithms and tools)
MS or PhD in Computer Science or Computer Engineering. Exceptional candidates with degrees in other disciplines will be considered.
Good working knowledge of how to exploit underlying computer architecture to achieve soft real-time goals.
A solid understanding of Git.
Strong familiarity with algorithms and how to choose an approach given the time and space requirements.
Decent knowledge of OS (Linux, Mac OS X, Windows) internals affect performance.
Excellent communication skills.
Ability to work in a collaborative environment.
Experience with distributed computing platforms such as Hadoop and Spark
Experience programming GPUs
Previous employment in an ML-focused engineering team
Locations: United States; California; San Francisco
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