Data Scientist

The Amatriot Group

Crane (IN)

On-site

USD 80,000 - 95,000

Full time

11 days ago
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Job summary

The Amatriot Group is seeking a Data Scientist to support the Navy’s CLIPS program by handling live imagery data, labeling, and ontology refinement. You will work on Linux-based AI/ML and computer vision workflows, and help define metadata schemas for complex video labeling.

On-site at NSWC Crane with travel, you will collaborate with government customers and engineers. Responsibilities include developing scalable data pipelines, documenting processes, and ensuring compatibility with large

Qualifications

  • Experience with modern database design and management.
  • Applied AI/ML for image processing.
  • Experience with computer hardware.
  • Experience with computer networking.

Responsibilities

  • Provide annotated and labeled video from Naval Imagery Collection Services (NICS) collections, including descriptors of scene content, collection pedigree, and AI/CV-assisted target labeling of targets within the video.
  • Provide recommendations for improving the fidelity in the ontology, which may include incorporating other data sources such as AIS, ADS-B, etc.
  • Develop and deploy AI/ML and computer Vision workflow tools within Linux environments to support military motion imagery and analysis.
  • Define metadata requirements and schemas to support the complex labeling of military motion imagery and live video streams.
  • Develop metadata tools, automated scripts, and models to support streamlined imagery labeling and video processing pipelines.
  • Develop efficient, Linux-compatible processes and tools for large-scale dataset preparation and dissemination.
  • Develop and implement data models in various formats to support the growth of NICS toolsets and the richness of data captured during data collections; provide documentation, processes, and tools to perform this task.
  • Identify, troubleshoot, and perform NICS hardware and Linux-based software upgrades to support evolving video collection requirements.

Skills

Linux environments
Computer vision architectures
Camera video processing pipelines
C++/Python programming
AI/ML for image processing
Written communication
Software development teamwork
EO domain knowledge

Tools

Databases
Networking

Job description

  • This represents the potential salary range for this position depending on education level, years of experience and/or certifications in addition to other position specific requirements which may impact salary

Location: Crane, IN

Security Clearance: Secret

Job Type: Full-Time

Target Salary Range*: $80,000-95,000

Position Overview

Amatriot is seeking a Data Scientist to provide engineering and technical support to assist our government customer with the collection of Live Imagery Products for Standardization (CLIPS) within the Department of Navy Electro-Optic (EO) Science and Technology (S&T) community. Products will support algorithm development on Unmanned Surface Vehicles (USV) and other customers. You will demonstrate competent knowledge of Linux systems, computer vision and camera operations.

Key Responsibilities
Technical Analysis and Evaluation
  • Provide annotated and labeled video from Naval Imagery Collection Services (NICS) collections, including descriptors of scene content, collection pedigree, and AI/CV-assisted target labeling of targets within the video.
  • Provide recommendations for improving the fidelity in the ontology, which may include incorporating other data sources such as AIS, ADS-B, etc.
  • Develop and deploy AI/ML and computer Vision workflow tools within Linux environments to support military motion imagery and analysis.
  • Define metadata requirements and schemas to support the complex labeling of military motion imagery and live video streams.
  • Develop metadata tools, automated scripts, and models to support streamlined imagery labeling and video processing pipelines.
  • Develop efficient, Linux-compatible processes and tools for large-scale dataset preparation and dissemination.
  • Develop and implement data models in various formats to support the growth of NICS toolsets and the richness of data captured during data collections; provide documentation, processes, and tools to perform this task.
  • Identify, troubleshoot, and perform NICS hardware and Linux-based software upgrades to support evolving video collection requirements.
Documentation and Standardization
  • Review documentation and community feedback to generate a holistic ontology that captures the variety of scene content, enabling applications based on visual cues from motion imagery.
Testing and Support
  • Perform onsite data collection at scheduled test events using NICS camera and sensor hardware.
  • Attend local meetings and training in support of the effort.
  • Support LXN with engineering services as required.
Travel and On-Site Support
  • Travel is expected to be required in performance of this task.
  • Be present on-site at NSWC Crane to support the effort with occasional telework authorized for weather, illness/recovery or defined special projects.
Qualifications
Experience
  • Experience with modern database design and management.
  • Applied Artificial Intelligence/Machine Learning (AI/ML) for image processing.
  • Experience with computer hardware.
  • Experience wit h computer networking.
Skills
  • Excellent writing and communication skills pertaining to business planning and project development.
  • An advanced level of knowledge and experience with Linux environments, Computer Vision (CV) architectures, and camera video processing pipelines.
  • Experience working within a software development team.
  • Coding experience in any major programing language.
  • A basic understanding of Electro-Optic technical operational procedures and requirements.
  • Knowledge of the government communities that work in and with EO.
  • Advance computer programming language experience with C++/or Python.
Certifications
  • Information assurance Technical (IAT) Level II. Minimum Certification requirements must be met prior to performance and maintained throughout the period of performance.
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