The Leidos Innovations Center (LInC) is looking for a Research Scientist in the area of Machine Learning (ML) who has a proven track record in developing technology-based approaches that yield novel, innovative capabilities while advancing the state of the art. 

Please note: This position can support remote/teleworking, however selected candidate must be willing to travel at least 25%. Preference will be given to candidates who are local to the Northern Virginia area.

Primary Responsibilities

The innovative technical solutions will advance the state of the art in machine learning and/or artificial intelligence while addressing long-term problems of importance to national security.  As such, candidates should have successful, proven, and demonstrable experience:

• Leading proposals, winning competitive research, and development efforts, and then leading high-performing teams in the development and integration of software-based solutions for customers such as DARPA, IARPA and other branches of the Department of Defense and Intelligence Community. 
• Serve in the role of principal investigator on contract R&D and internal R&D programs.
• Engage R&D customers and transition partners to develop new business opportunities and leading teams of researchers and engineers in the development, adaptation, and extension of innovative ML-based approaches and solutions across a range of technical areas and application domains, for diverse and often disparate types of data and complexity, and for projects that are inherently both fundamental and applied in nature. 
• Have a hands-on role and expected to customize and create various machine learning algorithms to operate over multi-domain data and optimizing the performance of those algorithms on the data.  
• Develop expertise in one or more technical domains, demonstrating ability to automate, extract, and prepare features from multi-domain datasets as well as modify and optimize various models within their technical domain. For example, they may adapt NLP libraries/toolkits that include transformer models like BERT and ChatGPT, as well as Stanford CoreNLP, Spacy, NLTK, Word2Vec, and Gensim for linguistics application or models like SSD, YOLO, DINO, and  Faster-RCNN for computer vision tasks.

Basic Qualifications

We are seeking a dynamic and entrepreneurial technical leader to drive our DARPA customer engagements and develop innovative technical solutions.  This candidate should be able to identify emerging technologies and evaluate the adaptation of these technologies to DoD use cases.  

• B.S in Electrical Engineering, Computational Linguistics, Computer Science, Mathematics,  or related technical field. with 12+ years of prior relevant experience, M.S degree with 10+ years of prior relevant experience, or Ph.D. with 8+ years of experience (Ph.D. preferred)
• Proven track record in proposing, winning, and executing work with customers such as DARPA/IARPA within the last 5 years. 
• Industrial/academic experience advancing the state-of-the-art machine learning-based research through demonstrable, verifiable technical results in their technical domain area  (e.g., NLP, CV, etc.) 
• At least 5 years of hands-on experience adapting the following technologies in the development of novel technology-based approaches as part of research projects: NumPy, SciPy, scikit-learn, TensorFlow, Pytorch, Keras, Genism, OpenCV, etc.
• Strong and proven customer relationship skills including the ability to discover the true technical challenges and requirements associated with opportunities, recommending alternative technical approaches, and shaping future opportunities.
• Understanding of transformers and foundation models
• Python proficiency
• Proficiency in developing, training, and deploying models both in Cloud platforms as well as on-prem resources.  Any experience deploying models on Size, Weight, and Power (SWaP) constrained platforms is highly desired.
• Self-starter with high intellectual curiosity
• Great communication skills, able to explain model training and performance results to a non-technical audience
• Proficient in data exploration techniques and tools
• Must be a U.S Citizen
• Ability to obtain a DoD Secret clearance with potential eligibility for Top Secret

Preferred Qualifications

• Ph.D. in Electrical Engineering, Computational Linguistics, Computer Science, Mathematics, or related technical field. 
• Track record of extending ML and AI tools and algorithms for new challenges 
• Experience applying and leading the application of ML/AI-based approaches and techniques in fundamental research contexts, to problems in complex domains, under conditions of uncertainty, and dynamic and evolving technical challenges  
• Ability to work in a fast-paced environment 
• Excellent written and oral skills in communicating technical information with an ability to present complex technical information clearly and coherently 
• Proven experience forming strong teams composed of members from academia and industry for competitive research and development opportunities.
• Experience operating within agile project execution environments and proficiency with agile tools (e.g., JIRA)
• Practical understanding of generative models
• Experience programming machine learning algorithms for GPUs
• Understanding of Convolutional Neural Nets
• Experience adapting large language models technologies 
• Discernment of when and how to use machine learning regulation
• Experience adapting ML algorithms and tools with operational workflows for customers in the US government
• Local to the Northern Virginia area

LInC

Original Posting Date:

While subject to change based on business needs, Leidos reasonably anticipates that this job requisition will remain open for at least 3 days with an anticipated close date of no earlier than 3 days after the original posting date as listed above.

Pay Range:

The 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.