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Machine Learning Research Scientist - Virginia, United States - Leidos
Description
The Leidos Innovation Center (LInC) Intelligent Sensors Branch has an opening for a Machine Learning Research Scientist to support a variety of government R&D projects focused developing machine learning (ML) algorithms for advanced sensors, imaging systems, and information operations platforms.
The candidate will work with teams within the LInC and across Leidos to plan and execute work that brings advanced machine learning & complex data science to bear on technical, high-dimensionality sensor data.
Additionally, the candidate must be able to compile developmental results into various reporting formats and communicate technical outcomes to technical and non-technical audiences.
The innovative solutions that Leidos delivers to customers advance the state of the art while addressing long-term problems of importance to national security.
Primary Responsibilities:
Support complex data-driven development projects involving technical sensor data and modern ML architectures
Implement sophisticated feature extraction techniques from complex, high-dimensional, datasets
Produce and communicate reports that summarize technical results to technical and non-technical audiences
Stay up to date with current state-of-the-art data science/ML methods and work with team to employ these methods within current and future R&D projects.
Basic Qualifications:
Masters degree in computer science, data science, engineering, or a physical science with 2-6 years of relevant experience or Ph.
Proficiency in Python, PyTorch, Tensorflow, Pandas, and Scikit-learn
Experience solving a variety of machine learning problems (e.g., supervised and unsupervised learning techniques, Bayesian modeling and inference, statistical estimation)
Experience with developing, deploying, and maintaining MLOps and CI/CD pipelines, ML experiment logging/tracking (e.g., MLFlow), and version-controlled datalakes (e.g., AWS S3, LakeFS, DVC)
Experience with ML model explainability/interpretability, generative AI, graph machine learning, or ML model deployment in resource constrained environments
Ability to work in a collaborative team environment utilizing agile methodologies
Qualified candidates must be a US Citizen and able to obtain a Top Secret security clearance (no clearance needed to start)
Preferred Qualifications:
Experience applying ML for the defense sector to sensor data from one of the following domains: CBRNE (chemical, biological, radiological, nuclear, and explosives), seismic, acoustic, magnetic, or imaging
Experience with formal proofs of algorithm performance / optimality
Original Posting Date:
Description
The Leidos Innovation Center (LInC) Intelligent Sensors Branch has an opening for a Machine Learning Research Scientist to support a variety of government R&D projects focused developing machine learning (ML) algorithms for advanced sensors, imaging systems, and information operations platforms.
The candidate will work with teams within the LInC and across Leidos to plan and execute work that brings advanced machine learning & complex data science to bear on technical, high-dimensionality sensor data.
Additionally, the candidate must be able to compile developmental results into various reporting formats and communicate technical outcomes to technical and non-technical audiences.
The innovative solutions that Leidos delivers to customers advance the state of the art while addressing long-term problems of importance to national security.
Primary Responsibilities:
Support complex data-driven development projects involving technical sensor data and modern ML architectures
Implement sophisticated feature extraction techniques from complex, high-dimensional, datasets
Utilize MLOps pipelines to develop/train/test/validate/deploy ML models
Produce and communicate reports that summarize technical results to technical and non-technical audiences
Stay up to date with current state-of-the-art data science/ML methods and work with team to employ these methods within current and future R&D projects.
Basic Qualifications:
Masters degree in computer science, data science, engineering, or a physical science with 2-6 years of relevant experience or Ph.
Proficiency in Python, PyTorch, Tensorflow, Pandas, and Scikit-learn
Experience solving a variety of machine learning problems (e.g., supervised and unsupervised learning techniques, Bayesian modeling and inference, statistical estimation)
Experience with developing, deploying, and maintaining MLOps and CI/CD pipelines, ML experiment logging/tracking (e.g., MLFlow), and version-controlled datalakes (e.g., AWS S3, LakeFS, DVC)
Experience with ML model explainability/interpretability, generative AI, graph machine learning, or ML model deployment in resource constrained environments
Ability to work in a collaborative team environment utilizing agile methodologies
Qualified candidates must be a US Citizen and able to obtain a Top Secret security clearance (no clearance needed to start)
Preferred Qualifications:
Experience applying ML for the defense sector to sensor data from one of the following domains: CBRNE (chemical, biological, radiological, nuclear, and explosives), seismic, acoustic, magnetic, or imaging
Experience with formal proofs of algorithm performance / optimality
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:
Pay Range $81, $146,875.00
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.
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