Leidos's Autonomy and Analytics (AAA) Division currently has an opening for a Senior Researcher specializing in Machine Learning in Arlington, VA . It is preferred that you have a TS/SCI however if you don't, you will be required to obtain a TS/SCI clearance. We are looking for you, a talented, high energy Machine Learning (ML) researchers eager to join a smart, diverse, and experienced team of Ph.D. level peers performing cutting-edge research and developing innovative technical solutions to deliver next generation Artificial Intelligence (AI) capabilities that address problems of national importance.
As our Machine Learning (ML) Senior Researcher, you'll work within the Leidos Innovation Center (LInC) performing basic and applied research in ML and developing solutions on larger programs as part of a team of 20+ fellow researchers. You'll take on the challenges of processing, interpreting and analyzing large volumes of data, including text, images and other media. You'll blend your research and operational experience in order to apply machine learning models and deep learning approaches to the problem of recognition in complex environments given sparse or limited training data. You will develop solutions that help make AI systems more secure, reliable, unbiased, and transparent. You will provide research direction and project leadership, develop innovative concepts for further exploration, and implement solutions that extend the state of the art for applications that range from automatic image recognition to text classification.
This might be the right fit for you if:
- You're tired of being the only person in your team who knows what GAN, LSTM, and CNN mean or where they can be used...
- You're more interested in using AI and ML to safeguard our nation's cybersecurity, improve our air traffic control systems, and develop targeted cancer treatments than you are in selling ads or recommending what type of toasters to buy...
- You're excited to work with customers like DARPA and IARPA defining, pursuing, and executing programs that combine your understanding of real-world problems with your ability to develop fundamental advances in ML that help solve those problems
- You like working independently to design and undertake new research as well as partner in a team environment across organizations.
- You like to develop topics for creative and innovative R&D approaches to solving major AI/ML challenges and work with potential sponsors (customers or internal champions) to secure funding for new research efforts based on those topics
- You want to lead teams of fellow researchers, data scientists, data engineers, and software engineers to execute complex R&D programs
- You enjoy design and implement secure, scalable, and fault-tolerant solutions across a distributed architecture, with the objective of researching and developing machine learning approaches, especially deep learning, applicable across multiple domains.
To be successful in this role you will need these skills:
- Master's Degree (Ph.D highly desired) in computer science, data science, machine learning, or a related discipline, such as statistics or applied mathematics with at least 10 years of applicable experience.
- At least three years of specialized experience innovating machine learning techniques and performing analytical functions using machine-learning libraries and approaches.
- Must be able to obtain a TS/SCI clearance.
- 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.
- Leadership abilities necessary to lead projects.
- Strong data analysis skills using R or a comparable platform, and one programming language, e.g. Python, Perl, C/C++, Java
You will wow us even more if you have these skills:
- TS/SCI clearance
- 8 years of overall experience is preferred
- PhD in Machine Learning or Artificial Intelligence with publication track record
- Prior experience as a project lead, preferably as PI
- Familiarity with existing deep learning libraries (e.g., TensorFlow, Spark, Theano, PyTorch, Scikit-learn, Keras, Caffe, Nvidia Digits) and collaboration environments (e.g. Jupyter notebooks, PyCharm)
- Prior experience with many of the following models: Deep Learning (CNNs, RCNNs, LSTMs), GANs, Autoencoders, Reinforcement Learning, Siamese Networks, Logistic Regression, Linear Regression, Support Vector Machines, Hidden Markov Models, Conditional Random Fields, Latent Dirichlet Allocation
- Experience in deploying models and optimizing performance on GPUs and other specialized HW.
External Referral Eligible