About Us: GE Ventures is creating a new start-up, AIROS. This Start-up will have access to unparalleled resources through GE’s Global Research Center, GE Digital, GE Aviation Systems (GEAS) and GE’s IoT platform, Predix, NBC team leverages GE’s operational excellence, brand and scale to create options for breakout growth. The NEWCO is creating enabling infrastructure and robotics technologies that promote autonomy with persistent, geospatial big data stacks.
AIROS offers a great work environment, professional development, challenging careers, and competitive compensation. AIROS 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.
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 Sr. Staff Machine Learning/AI Scientist will work in and lead teams as technical expert to design and develop predictive algorithms based on statistical foundations, efficient algorithms for planning and scheduling, and scalable approaches for coordination of distributed decision agents. The successful candidate will be skilled in developing techniques and methods to support predictive analysis and decision making in online and dynamic environment with real-time constraints.
Essential Responsibilities: In this role, you will:
Work with Engineering Leadership, Product and Business Managers to understand product capability needs, and translate those into algorithm designs
Provide expertise, guidance and rationale in the selection of context appropriate algorithms designs
Work as part of a cross-functional team to translate algorithm design into practical and efficient implementations for commercially viable products and services.
Provide expertise in the development of statistically driven predictive techniques, and support their translation into online software functions.
Develop novel approaches for planning and scheduling operation of autonomous systems managed by distributed agents.
Devise new strategies for scaling the coordinated operations of autonomous entities in environments with real-time constrains and safety concerns.
Generate reports, annotated code, and other projects artifacts to document, archive, and communicate your work and outcomes.
Participate in industry and technical meetings to support business objectives
Communicate methods, findings, and hypotheses with stakeholders
Master’s Degree in a “STEM” major (Science, Technology, Engineering, Mathematics) plus 7 years analytics development for industrial applications in a commercial/industrial setting OR Ph.D. in a “STEM” major (Science, Technology, Engineering, Mathematics) plus 3 year analytics development for industrial applications in a commercial/industrial setting
Demonstrated expertise in the use of one or more analytic software tools or languages (e.g., SAS, SPSS, R, Python)
Expertise in statistical data processing and algorithms
Knowledge of heuristic and optimal methods for planning problems
Understanding of prediction techniques in noisy, disrupted, and/or uncertain environments
Prior experience with one or more scientific/statistical computation frameworks such as Matlab, Python, R
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.
Any offer of employment is conditioned upon the successful completion of a background investigation and drug screen
Must be willing to travel at least 10%
Must be willing to work out of an office located in Boston
PhD in Engineering or Scientific Discipline Experience working in and leading teams
Experience developing distributed algorithms
Experience with communicating and presenting to project/program leadership
Experience collaborating with external/industry partners
Experience developing novel and innovative technologies
Comfortable serving as a change agent
Comfortable working in ambiguous and dynamic environments
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