Basic Qualifications    Education Requirements:
Requires a Bachelor's degree in Engineering, or a related Science or Mathematics field. Also requires 5+ years of job-related experience, or a Master's degree plus 3 years of job-related experience.
Clearance Requirements:
Ability to obtain a Department of Defense Secret security clearance is required at time of hire. Applicants selected will be subject to a U.S. Government security investigation and must meet eligibility requirements for access to classified information. Due to the nature of work performed within our facilities, U.S. citizenship is required.
Responsibilities for this Position   The Deep Learning Analytics Center of Excellence (DLA CoE) at General Dynamics Mission Systems is actively seeking a data scientist with a background in Deep Learning (DL), advanced data visualization, software development, and full Machine Learning (ML) life cycle management. This individual serves in a pivotal role that interfaces directly with our business development teams, aiding in identifying and cultivating of innovative ML initiatives. Furthermore, the role entails the responsibility of engaging with our clientele, educating them about what AI can and cannot do, our approach to problem solving, and our progress to date on their programs.
They will collaborate closely with our interdisciplinary teams to tackle complex DL challenges. This involves leveraging and refining cutting-edge training methodologies and model architectures to solve problems across a diverse range of data modalities underwater, on land, in the air, and in space.
Candidates for this position are expected to demonstrate a high level of technical acumen, excellent communication skills, and a passion for continuous learning within the ever-evolving field of artificial intelligence.
Our Commitment to You:
A workplace that allows you to take your career to the next level.
Access to expansive and diverse datasets to grow your data science portfolio.
Applied research oriented work, alongside award winning teammates to develop practical solutions that directly impact the company's bottom line.
Training budget to help you develop your professional skills, attending conferences, obtaining certifications, even a masters degree.
Flexibility to fully manage your own schedule including a hybrid work schedule to allow for a blend of in office and remote work.
Opportunities & encouragement to patent and/or publish your work.
What You'll Do:
Collaborating with teams of data scientists on full life cycle data-driven solutions.
Data wrangling, preprocessing, and manipulation for ML applications.
Applying advanced statistical methods and reporting techniques to large datasets.
Interpreting data analysis and experimental results, and communicating insights.
Developing ML systems for both supervised and unsupervised learning tasks.
Mastering deep learning algorithms and addressing their limitations related to hardware or data.
Conducting experiments to enhance model performance and clearly reporting outcomes to both technical and non-technical audiences.
Optimizing DL architectures for performance and supporting systematic optimization efforts.
Deploying ML solutions across diverse platforms, from large clusters to small SWaP (Size, Weight, and Power) environments.
Monitoring ongoing model performance to detect and adjust for data drift.
Following best practices for software documentation and reporting.
Skills You'll Bring:
Proficiency in ML and DL frameworks, such as scikit-learn, TensorFlow, and PyTorch.
Excellent written and verbal communication abilities.
Experience with the Linux command line, including bash and shell scripting.
Expertise in handling large, complex datasets including image, cyber, NLP, and signal data.
Experience in distributed version control systems and DevOps tools, such as GitLab, Git, Docker, and Kubernetes.
Skills in data preparation and corpus filtering using databases like PostgreSQL and MySQL.
Software development experience in multiple programming languages, with an emphasis on Python.
Understanding of validation methods for ML models.
Familiarity with experimental design for data science projects.
Competence in full life cycle ML operations (MLOps).
Target salary range: USD $138,680.00/Yr. - USD $153,849.00/Yr. This estimate represents the typical salary range for this position based on experience and other factors (geographic location, etc.). Actual pay may vary. This job posting will remain open until the position is filled.
Company Overview   General Dynamics Mission Systems (GDMS) engineers a diverse portfolio of high technology solutions, products and services that enable customers to successfully execute missions across all domains of operation. With a global team of 12,000+ top professionals, we partner with the best in industry to expand the bounds of innovation in the defense and scientific arenas. Given the nature of our work and who we are, we value trust, honesty, alignment and transparency. We offer highly competitive benefits and pride ourselves in being a great place to work with a shared sense of purpose. You will also enjoy a flexible work environment where contributions are recognized and rewarded. If who we are and what we do resonates with you, we invite you to join our high-performance team!

Equal Opportunity Employer / Individuals with Disabilities / Protected Veterans

Basic Qualifications
Education Requirements:
Requires a Bachelor's degree in Engineering, or a related Science or Mathematics field. Also requires 5+ years of job-related experience, or a Master's degree plus 3 years of job-related experience.
Due to the nature of work performed within our facilities, U.S. citizenship is required.
Responsibilities for this Position
The Deep Learning Analytics Center of Excellence (DLA CoE) at General Dynamics Mission Systems is actively seeking an experienced mid-level data scientist with experience in Deep Learning (DL), software development, and MLOps life cycle management. This individual serves in a pivotal role that interfaces directly with our business development teams, aiding in identifying and cultivating innovative ML initiatives. Furthermore, the role entails the responsibility of engaging with our clientele, educating them about what AI can and cannot do, our approach to problem-solving, and our progress to date on their programs.
They will collaborate closely with our interdisciplinary teams to tackle complex DL challenges. This involves leveraging and refining cutting-edge training methodologies and model architectures to solve problems across a diverse range of data modalities underwater, on land, in the air, and in space.
Candidates for this position are expected to demonstrate a high level of data science acumen, excellent communication skills, and a passion for continuous learning within the ever-evolving field of artificial intelligence.
Our Commitment to You:
A workplace that allows you to take your career to the next level.
Access to expansive and diverse datasets to grow your data science portfolio.
Applied research-oriented work, alongside award-winning teammates to develop practical solutions that directly impact the company's bottom line.
Training budget to help you develop your professional skills, attending conferences, obtaining certifications, even a master's degree.
Flexibility to fully manage your own schedule including a hybrid work schedule to allow for a blend of in-office and remote work.
Opportunities & encouragement to patent and/or publish your work.
What You'll Do:
Collaborating with teams of data scientists on full life cycle data-driven solutions.
Data wrangling, preprocessing, and manipulation for ML applications.
Applying advanced statistical methods and reporting techniques to large datasets.
Interpreting data analysis and experimental results, and communicating insights.
Developing ML systems for both supervised and unsupervised learning tasks.
Mastering deep learning algorithms and addressing their limitations related to hardware or data.
Conducting experiments to enhance model performance and clearly reporting outcomes to both technical and non-technical audiences.
Optimizing DL architectures for performance and supporting systematic optimization efforts.
Deploying ML solutions across diverse platforms, from large clusters to small SWaP (Size, Weight, and Power) environments.
Monitoring ongoing model performance to detect and adjust for data drift.
Following best practices for software documentation and reporting.
Skills You'll Bring:
Proficiency in ML and DL frameworks, such as scikit-learn, TensorFlow, and PyTorch.
Excellent written and verbal communication abilities.
Experience with the Linux command line, including bash and shell scripting.
Expertise in handling large, complex datasets including image, cyber, NLP, and signal data.
Experience in distributed version control systems and DevOps tools, such as GitLab, Git, Docker, and Kubernetes.
Skills in data preparation and corpus filtering using databases like PostgreSQL and MySQL.
Software development experience in multiple programming languages, with an emphasis on Python.
Understanding of validation methods for ML models.
Familiarity with experimental design for data science projects.
Competence in full life cycle ML operations (MLOps).
Target salary range:  USD $119,752.00 / Yr. - USD $132,849.00 / Yr. This estimate represents the typical salary range for this position based on experience and other factors (geographic location, etc.). Actual pay may vary. This job posting will remain open until the position is filled.
Company Overview
General Dynamics Mission Systems (GDMS) engineers a diverse portfolio of high technology solutions, products, and services that enable customers to successfully execute missions across all domains of operation. With a global team of 12,000+ top professionals, we partner with the best in industry to expand the bounds of innovation in the defense and scientific arenas. Given the nature of our work and who we are, we value trust, honesty, alignment, and transparency. We offer highly competitive benefits and pride ourselves in being a great place to work with a shared sense of purpose. You will also enjoy a flexible work environment where contributions are recognized and rewarded. If who we are and what we do resonates with you, we invite you to join our high-performance team!
Equal Opportunity Employer / Individuals with Disabilities / Protected Veterans

#J-18808-Ljbffr

Basic Qualifications    Education Requirements:
Requires a Bachelor's degree in Engineering, or a related Science or Mathematics field. Also requires 5+ years of job-related experience, or a Master's degree plus 3 years of job-related experience.
Due to the nature of work performed within our facilities, U.S. citizenship is required.
Responsibilities for this Position   The Deep Learning Analytics Center of Excellence (DLA CoE) at General Dynamics Mission Systems is actively seeking an experienced mid-level data scientist with  experience in Deep Learning (DL) , software development,  and MLOps life cycle management . This individual serves in a pivotal role that interfaces directly with our business development teams, aiding in identifying and cultivating innovative ML initiatives. Furthermore, the role entails the responsibility of engaging with our clientele, educating them about what AI can and cannot do, our approach to problem-solving, and our progress to date on their programs.
They will collaborate closely with our interdisciplinary teams to tackle complex DL challenges. This involves leveraging and refining cutting-edge training methodologies and model architectures to solve problems across a diverse range of data modalities underwater, on land, in the air, and in space.
Candidates for this position are expected to demonstrate a high level of data science acumen, excellent communication skills, and a passion for continuous learning within the ever-evolving field of artificial intelligence.
Our Commitment to You:
A workplace that allows you to take your career to the next level.
Access to expansive and diverse datasets to grow your data science portfolio.
Applied research-oriented work, alongside award-winning teammates to develop practical solutions that directly impact the company's bottom line.
Training budget to help you develop your professional skills, attending conferences, obtaining certifications, even a masters degree.
Flexibility to fully manage your own schedule including a hybrid work schedule to allow for a blend of in office and remote work.
Opportunities & encouragement to patent and/or publish your work.
What You'll Do:
Collaborating with teams of data scientists on full life cycle data-driven solutions.
Data wrangling, preprocessing, and manipulation for ML applications.
Applying advanced statistical methods and reporting techniques to large datasets.
Interpreting data analysis and experimental results, and communicating insights.
Developing ML systems for both supervised and unsupervised learning tasks.
Mastering deep learning algorithms and addressing their limitations related to hardware or data.
Conducting experiments to enhance model performance and clearly reporting outcomes to both technical and non-technical audiences.
Optimizing DL architectures for performance and supporting systematic optimization efforts.
Deploying ML solutions across diverse platforms, from large clusters to small SWaP (Size, Weight, and Power) environments.
Monitoring ongoing model performance to detect and adjust for data drift.
Following best practices for software documentation and reporting.
Skills You'll Bring:
Proficiency in ML and DL frameworks, such as scikit-learn, TensorFlow, and PyTorch.
Excellent written and verbal communication abilities.
Experience with the Linux command line, including bash and shell scripting.
Expertise in handling large, complex datasets including image, cyber, NLP, and signal data.
Experience in distributed version control systems and DevOps tools, such as GitLab, Git, Docker, and Kubernetes.
Skills in data preparation and corpus filtering using databases like PostgreSQL and MySQL.
Software development experience in multiple programming languages, with an emphasis on Python.
Understanding of validation methods for ML models.
Familiarity with experimental design for data science projects.
Competence in full life cycle ML operations (MLOps).
Target salary range: USD $119,752.00/Yr. - USD $132,849.00/Yr. This estimate represents the typical salary range for this position based on experience and other factors (geographic location, etc.). Actual pay may vary. This job posting will remain open until the position is filled.
Company Overview   General Dynamics Mission Systems (GDMS) engineers a diverse portfolio of high technology solutions, products and services that enable customers to successfully execute missions across all domains of operation. With a global team of 12,000+ top professionals, we partner with the best in industry to expand the bounds of innovation in the defense and scientific arenas. Given the nature of our work and who we are, we value trust, honesty, alignment and transparency. We offer highly competitive benefits and pride ourselves in being a great place to work with a shared sense of purpose. You will also enjoy a flexible work environment where contributions are recognized and rewarded. If who we are and what we do resonates with you, we invite you to join our high-performance team!

Equal Opportunity Employer / Individuals with Disabilities / Protected Veterans

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