Location(s): United States; California, New York; Niskayuna, San Ramon
About Us: GE is the world's Digital Industrial Company, transforming industry with software-defined machines and solutions that are connected, responsive and predictive. Through our people, leadership development, services, technology and scale, GE delivers better outcomes for global customers by speaking the language of industry.
At GE Global Research, we’re redefining what’s possible. From cutting-edge research in molecular pathology for use in personalized cancer diagnostics to programs in coal gasification and renewable power that drive clean energy solutions, our work at Global Research is world-renowned. As part of our team, you’ll find yourself among nearly 3,000 scientists and engineers from every discipline in a dynamic atmosphere where you’ll be constantly challenged to learn and grow. You’ll have access to leaders on all levels of the organization and collaborate across the globe with the very best in the field. If you have an insatiable intellectual curiosity and the ability to articulate your vision, then join us and watch the work you do create the next generation of products and processes that will impact the globe for generations to come.
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: Are you looking for meaningful work? Beyond ad placement and curating personal “likes” profiles? Work on problems in Healthcare, Aviation, or Renewable Energy? To solve real problems, many different skills need to come together. That is why we come together as a team to solve the toughest and most impactful industrial problems.
Essential Responsibilities: You will collaborate with world-class technological leaders from many different disciplines. You will be immersed in an interdisciplinary team, you will continuously learn from the different way other experts think, and your contributions will make a difference.
Collaborate with Senior Machine Learning Researchers and world-class multidisciplinary teams to address supervised and unsupervised leaning problems in an applied research environment. Develop & deploy modern machine learning, artificial intelligence and statistical methods (clustering and classification algorithms, deep learning, transfer learning, adversarial learning, active learning, continuous learning, explanation learning, etc) for finding patterns/models from real-world industrial data. Familiarity with large data sets, cloud based development and deployment, open source practices and frameworks and experience in putting intelligent applications in production are desirable.
In this role, you will:
Develop and deploy machine learning algorithms/solutions to solve industrial problems at GE
Determine methodologies needed; apply such methodologies (e.g. Neural Nets, Deep Learning, Active Learning, Random Forest, Bayesian methods, etc.) on monitoring, classification, prognostics, optimization and related research domains.
Define data needs, evaluate data quality, perform and critique appropriate statistical analyses using software such as Python, MATLAB, R, TensorFlow etc. Explore, determine & develop technical approaches to be used and apply them on major challenges
Interface closely with GE Business counterparts to understand/define requirements, domain knowledge/models, and data needs
Effectively communicate technical analyses and results
Support proposals to respond to internal as well as external funding opportunities
Doctorate Degree in Computer Science, Mathematics, Applied Statistics, Operations Research or Engineering OR Master’s Degree in Computer Science, Mathematics, Applied Statistics, Operations Researcher or Engineering with a minimum of 3 years of experience applying theoretical or experiential knowledge on machine learning & artificial intelligence to solve real world problems
Foundation in theories underlying machine learning and artificial intelligence techniques
Ability to apply theoretical or experiential knowledge on machine learning to solve industrial problems
Experience in developing machine learning packages with modern programming languages e.g. Python, R, Scala, Java, MATLAB, C++ etc.
Legal authorization to work in the U.S. is required. We will not sponsor individuals at the Masters level for employment visas, now or in the future, for this job opening.
Must be willing to work out of an office located in Niskayuna, NY or San Ramon, CA
Must be 18 years or older.
You must submit your application for employment on the careers page at www.gecareers.com to be considered.
Experience in applying machine learning and artificial intelligence to industrial problems
Programming skills/ experience in high level languages like Java, .NET, and Cloud computing
Knowledgeable with relational databases & SQL concepts
Strong working knowledge and experience working with big data technology e.g. Spark, Hadoop and MapReduce
Interest/Experience in large data sets, cloud based architectures and deployment frameworks for machine learning algorithms
Strong analytical skills, with demonstrated reputation including publications / development / deployment experience
Hands on experience with medium scale distributed compute infrastructure deployment is a plus
Excellent teamwork and customer focus
Excellent written and verbal communication skills
Ability to work under uncertainty
Ability to work independently with minimal direction
Flexibility of working across all functions/levels as part of a team
Locations: United States; California, New York; Niskayuna, San Ramon
We are in the process of transitioning to an improved job application system and in the interim we are operating with two systems. Have your Job ID ready (from the email you received when you applied) to log in and check your application status.
Click the appropriate button. If you don't know your job ID, you can still check your status: use both buttons.