Research Scientist – Multimodal Machine Learning
|Published||December 28, 2022|
|Location||Bethesda, United States of America|
The Leidos Innovation Center (LInC) Advanced Analytics team has an opening for a Machine Learning Research Scientist with a background in deep learning to integrate, adapt, and extend novel capabilities to address the customer’s research challenges in competitive contract and internal research and development (R&D) programs (basic and applied). Candidates with a deep technical background in multimodal machine learning, few-shot / one-shot / zero-shot learning, semi-supervised / self-supervised / weakly-supervised learning, learning on graphs, or recommender systems are strongly encouraged to apply.
We are looking for a scientist with a specialization in one of the program’s research focus areas to work with PhD-level peers to develop and implement approaches and solutions for contract research and development projects. The innovative technical approaches and solutions delivered to customers that advance the state of the art in the research while addressing long-term problems of importance to national security. The ideal candidate will have a proven track record of supporting all aspects of the program life cycle: supporting business development through the design of new research concepts and topics; writing technical approaches and plans as part of the proposal process; leading multi-discipline project teams and supporting project execution objectives; and transition of impactful, novel capabilities to stakeholders and the communities of practice at the project’s conclusion.
- Independently influence the development of approaches and solutions that address highly complex research challenges as well as partner in a team environment across organizations.
- Independently design and undertake new applications of research as well as partner in a team environment across organizations.
- Develop topics for novel and innovative R&D approaches to solving program challenges and work with potential sponsors (customers or internal champions) to secure funding for new research efforts based on those topics.
- Perform metrics-based evaluations of new technologies from research organizations to determine potential contributions.
- Lead teams of fellow researchers, data scientists, data engineers, and software engineers to execute complex R&D programs.
- Apply machine learning algorithms onto various problem sets
To be successful in this role you need these skills (required):
- Advanced degree (PhD highly desired) in machine learning, computer science, data science, or a related discipline, such as statistics or applied mathematics. Typically requires BS degree and 8+ years of prior relevant experience or Masters with 6+ years of prior relevant experience.
- Ability to program in Python
- Familiarity with common general and deep learning ML toolkits such as scikit-learn, PyTorch, Tensorflow, fastai, etc.
- Familiarity with common NLP ML toolkits such as stanza, genism, NLTK, spaCy, etc.
- Familiarity with common CV ML toolkits such as OpenCV, YOLO architectures, DeepFace, etc.
- Familiarity with collaboration environments (e.g. Jupyter notebooks, PyCharm, VSCode, CDSW)
- Demonstrable experience (both individually and leading/directing others in) adapting and extending open technologies in the context of novel machine learning approaches
- Experience leading technical projects to successful completion
- Knowledge of state-of-the-art methods coupled with the creativity and intelligence to advance beyond them. Track record of active learning and creative problem solving
- With a Master’s degree, at least eight (8) years of specialized experience innovating analytical techniques and performing analytical functions using machine-learning libraries or other approaches. With a PhD, at least six (6) years of specialized experience is required.
- Top Secret Security clearance - current and active
- Previous experience as a technical lead, such as a principal investigator on a project
- Experience in one or more of the following
- Apply transfer learning to retrain or fine-tune existing models to novel datasets
- Multimodal machine and representation learning on highly heterogeneous data
- Few-shot, one-shot, and zero-shot learning techniques and applications in environments with limited access to labeled data
- Semi-supervised, self-supervised, and weakly-supervised learning techniques and applications in environments with limited access to labeled data
- Graph machine learning
- Building robust recommender systems for application end-users
- Multilingual NLP
Pay Range $97,500.00 - $150,000.00 - $202,500.00The Leidos pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
Leidos is a Fortune 500® technology, engineering, and science solutions and services leader working to solve the world’s toughest challenges in the defense, intelligence, civil, and health markets. The company’s 44,000 employees support vital missions for government and commercial customers. Headquartered in Reston, Virginia, Leidos reported annual revenues of approximately $13.7 billion for the fiscal year ended December 31, 2021. For more information, visit www.Leidos.com.
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