Sr. R&D Staff Computer Vision at Oak Ridge National Laboratory in Oak Ridge, Tennessee

Job Description:

Requisition Id4414

Position Overview
The National Security Sciences Directorate at Oakridge National Laboratory leads scientific and technological breakthroughs to confront some of the nation's most difficult security challenges. We develop interdisciplinary applications needed for the security of our nation today and target our vision on how these challenges may manifest themselves in a decade or more.

Our research and development focuses on cybersecurity and cyber physical resiliency, data analytics, geospatial science and technology, nuclear nonproliferation, and high-performance computing for sensitive national security missions. We also enhance ORNL contributions to national security challenges by working closely with leading researchers at the lab in areas such as nuclear and chemical sciences and engineering, applied materials, advanced manufacturing, biosecurity, transportation, and computing.

We are currently seeking qualified applicants for a Senior R&D Staff position in Computer Vision within our Geographic Data Science Section and GeoAI group. The position requires strong skills in machine learning and deep learning methods, application and architecture The position affords the unique opportunity to work with a talented interdisciplinary team of R&D professionals enabling true impact on critical national security missions. The Geographic Data Science Section Develops sensor technologies, analytical methods and models that collect, integrate, analyze and derive value from spatiotemporal data.

Within the GeoAI group, you will develop novel mathematical and computer science capabilities for curating, fusing, analyzing and deploying computer vision models on edge devices as well as one of the world's most robust high-performance computing platforms.


Major Duties and Responsibilities:
- Initiate, lead and perform independent and impactful R&D on an ongoing basis as evidenced by, for example, innovative S&T artifacts delivered to sponsors, publications, successful proposals, technical presentations and technology demonstrations, professional community engagement, inventions/patents/copyrights, etc.
- Develop and implement plans to exploit new opportunities and/or expand existing research efforts.
- Provide relevant input to assist the R&D Group Lead and Section Head with staff development while providing direct and impactful guidance to staff on regular basis.
- Lead by example by exercising scientific integrity in proposing, performing, and communicating research.
- Lead by example to ensure all work is carried out safely, securely, and in compliance with ORNL policies, standards, and procedures.
- Exemplify a commitment to excellence in research, operations, and community engagement, and work cooperatively to leverage scientific capabilities across ORNL.
- Advance the reputation of the group members and standing of the group as a whole through establishing collaborations, professional society leadership and involvement, and organization of technical events.
- Lead research projects to create curated datasets, formulate machine learning problems, and apply machine learning and computer vision techniques to solve real world problems with spatio-temporal data.
- Research and productionize state-of-the-art deep learning models such as object detection, semantic segmentations, classification, sequence modeling etc.
- Work in a highly collaborative environment with other data scientists, remote sensing scientists, engineers, physicists and geographers to deliver systems from prototyping to production level.


Basic Requirements:
- Requires a Ph.D. with a minimum of 6 years relevant experience, a M.S. with a minimum of 12 years experiences, B.S. with 15 years of experience and a focus on Computer Vision, Machine Learning or related fields
- Experience programming in Python, Scala or other production languages using tools like TensorFlow, SageMaker, Keras, PyTorch, AIML, and/or PetaStorm
- Qualified candidates should have demonstrated experience in geographic data science related research areas.
- Experience in productionizing machine learning models and deploying models on different platforms.
- Experience with Sklearn, LSTM, LDA, anomaly detection, entity extraction, summarization, multi-part learning, CNN's, RNN's, Deep Reinforcement Learning, GAN's. Self-Organizing Maps, Boltzman Machines, Backpropagation, Gradient Decsent and AutoEncoders, NLP.
- Excellent interpersonal skills with a demonstrated leadership ability and a strong commitment to a teaming environment.
- Strong written and oral communication skills.


Preferred Qualifications:
- Experience working with large spatial datasets, satellite imagery and time series analysis.
- Experience in Applied Mathematics, Cloud Computing, Bayesian Statistics
- Hands-on experience with training on infrastructures and frameworks such as GPUs, Spark, distributed Tensorflow etc.
- Hands-on experience with model deployment in cloud environments and edge devices
- Demonstrated track record in national and/or international engagements that seek to sustain and strengthen the geographic data science R&D community.
- Experience working for or collaborating with DOE National Laboratories, academic institutions, other research organizations and the private sector.
- Strong drive to learn new topics and skills, to develop innovative products for our customers, and build whatever is necessary along the way


Special Requirement:
This position requires the ability to obtain and maintain a clearance from the Department of Energy. As such, this position is a Workplace Substance Abuse (WSAP) testing designated position. WSAP positions require passing a pre-placement drug test and participation in an ongoing random drug testing program.

This position will remain open for a minimum of 5 days after which it will close when a qualified candidate is identified and/or hired.
We accept Word (.doc, .docx), Adobe (unsecured .pdf), Rich Text Format (.rtf), and HTML (.htm, .html) up to 5MB in size. Resumes from third party vendors will not be accepted; these resumes will be deleted and the candidates submitted will not be considered for employment.

If you have trouble applying for a position, please email ORNLRecruiting@ornl.gov.

ORNL is an equal opportunity employer. All qualified applicants, including individuals with disabilities and protected veterans, are encouraged to apply. UT-Battelle is an E-Verify employer..