Machine Learning Research Scientist

Key Skills

Java Programming, Python Programming, SQL, Tech Support, Data Mining, Deep Learning, Jupyter Notebook, Natural Language Processing (NLP), Computer Vision (CV), CNNs, Predictive Modeling, Random forests, PyCharm

Job Description

Are you ready to join Leidos all-star team? Through training, teamwork, and exposure to challenging technical work, let Leidos show how to accelerate your career path.

The Leidos Innovation Center (LInC) Advanced Analytics team has an opening for Research Scientist with experience and proven qualifications in designing and implementing state-of-the-art technical approaches for contract research and development projects for a range of customers to work in our Arlington, VA office. We are looking for someone who is capable of building and leading multidisciplinary teams composed of fellow research scientists, data scientists, software developers, and engineers from the proposal, execution, and transition stages of projects. Someone who specializes in machine learning and wants to join a team of Ph.D.-level peers on this mission. The innovative technical solutions delivered to customers advance the state of the art while addressing long-term problems of importance to national security. Our team has successful, proven, and demonstrable experience leading cross-discipline teams in the development and integration of software-based solutions for competitive, contract-based applied research programs. In this role you will need to have experience designing solutions for competitively sourced proposals and in forming teams of composed of industry, small businesses, and academic-based partners for contract R&D programs and directing teams of research scientists (including research scientists with backgrounds in machine learning, artificial intelligence, and embedded systems) in the design of sub-components, integration platforms, and testing and research validation methodologies and techniques. We are also looking for someone with experience developing solutions for a variety of machine learning problems (e.g., probabilistic modeling, learning techniques, statistical inference) and application areas (e.g., NLP, computer vision, data mining, cybersecurity, operations research).

This is your day to day:

• Collaborate with teammates across the organization, bringing diverse capabilities together to develop innovative solutions for contract research and development projects, both leading and sometimes working under the guidance of fellow researchers.
• Take on the challenges of processing, interpreting, and analyzing large volumes of data.
• Blend your research and operational experience in order to apply approaches to the problems of inference in complex operational environments given varying degrees of quality of data.
• To be successful in this role you need these skills (required):
• Bachelor's degree (Ph.D. highly desired) in engineering, computer science, data science, or a related discipline, such as economics, statistics, or applied mathematics with at least 8 years of specialized experience innovating analytical techniques and performing analytical functions using machine-learning libraries or other approaches. With a Ph.D., at least four years of overall experience is preferred.
• Must be able to obtain and maintain a TS/SCI.
• Track record of relevant publications in peer-reviewed conferences and journals.
• Knowledge of state-of-the-art methods coupled with the creativity and intelligence to advance beyond them.
• Experience in one or more subfields of ML or AI, such as: NLP, Computer Vision, Pattern Recognition, Predictive Modeling, Data Mining, Decision Support, Reduced Order Modeling.
• Leadership abilities necessary to lead projects.
• Strong data analysis skills and extensive experience with developing and prototyping algorithms in Python and/or Matlab.

Preferred qualifications:

• Previous experience as a technical lead, such as a principal investigator on a project
• Experience as a PI on projects for a competitive contract R&D customer, such as DARPA
• Familiarity with collaboration environments (e.g. Jupyter notebooks, PyCharm)
• Prior experience with many of the following models: Deep Learning (CNNs, RCNNs, LSTMs), GANs, Autoencoders, Reinforcement Learning, Probabilistic Modeling, Siamese Networks, Logistic Regression, Linear Regression, Support Vector Machines, Hidden Markov Models, Conditional Random Fields, Latent Dirichlet Allocation