Key responsibilities include:

• Supporting flight operations for aircraft, including operations planning, scheduling, and resource allocation to support development and customer-facing activities.
• Serving as Site Lead for flight test events, demonstrations, and operational deployments, coordinating personnel, aircraft, equipment, and logistics across multiple test locations.
• Developing comprehensive logistics plans for demonstrations, deployments, operations, and maintenance of systems across varied military and test environments.
• Coordinating with test engineers, pilots, program teams, and military partners to align logistics processes with test schedules, mission planning, and resource allocation.
• Managing demonstration and test inventory, equipment readiness, and site logistics to ensure continuous operational readiness.
• Collaborating with engineering teams to integrate logistical considerations into product design, development, and sustainment planning.
• Contributing to proposal development for new contracts, focusing on logistics and sustainment aspects.
• Analyzing and improving logistics and operations processes to enhance efficiency, reduce costs, and scale operations across expanding programs.

The ideal candidate will have a minimum of 4-5 years of experience in military and civilian airlift logistics, with a strong background in both ground and air support operations. They will also have proven experience in developing and implementing logistics strategies for complex military systems in line with Department of Defense (DoD) logistics processes, regulations, and standards.

XML job scraping automation by YubHub

A successful candidate will be skilled in developing real-time object detection, sensor fusion, and state estimation algorithms using data from diverse mission sensors such as EO/IR cameras, radars, and IMUs. The role requires strong algorithmic thinking, deep familiarity with airborne sensing systems, and the ability to deliver performant software in simulation and real-world conditions.

Shield AI is committed to developing cutting-edge autonomy for unmanned aircraft operating across all Department of Defense (DoD) domains, including air, sea, and land. Our Perception Engineers are instrumental in creating the situational awareness that underpins autonomy, ensuring our systems understand and respond to the operational environment with speed, precision, and resilience.

Responsibilities:

• Lead teams across autonomy, integration, and testing by aligning technical efforts, resolving cross-functional challenges, and driving mission-focused execution.
• Develop advanced perception algorithms for object detection, classification, and multi-target tracking across diverse sensor modalities.
• Implement sensor fusion frameworks by integrating data from vision systems, radars, and other mission sensors using probabilistic and deterministic fusion techniques.
• Develop state estimation capabilities by designing and refining algorithms for localization and pose estimation using IMU, GPS, vision, and other onboard sensing inputs.
• Analyze and utilize sensor ICDs to ensure correct data handling, interpretation, and synchronization.
• Optimize perception performance by tuning and evaluating perception pipelines for performance, robustness, and real-time efficiency in both simulation and real-world environments.
• Support autonomy integration by working closely with autonomy, systems, and integration teams to interface perception outputs with planning, behaviors, and decision-making modules.
• Validate in simulated and operational settings by leveraging synthetic data, simulation environments, and field testing to validate algorithm accuracy and mission readiness.
• Collaborate with hardware and sensor teams to ensure seamless integration of perception algorithms with onboard compute platforms and diverse sensor payloads.
• Drive innovation in airborne sensing by contributing novel ideas and state-of-the-art techniques to advance real-time perception capabilities for unmanned aircraft operating in complex, GPS-denied, or contested environments.
• Travel Requirement – Members of this team typically travel around 10-15% of the year (to different office locations, customer sites, and flight integration events).

Requirements:

• BS/MS in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, and/or similar degree, or equivalent practical experience.
• Typically requires a minimum of 10 years of related experience with a Bachelor’s degree; or 9 years and a Master’s degree; or 7 years with a PhD; or equivalent work experience.
• 7+ years of experience in Unmanned Systems programs in the DoD or applied R&D.
• 2+ years of people leadership experience.
• Background in implementing algorithms such as Kalman Filters, multi-target tracking, or deep learning-based detection models.
• Familiarity with fusing data from radar, EO/IR cameras, or other sensors using probabilistic or rule-based approaches.
• Familiarity with SLAM, visual-inertial odometry, or sensor-fused localization approaches in real-time applications.
• Ability to interpret and work with Interface Control Documents (ICDs) and hardware integration specs.
• Proficiency with version control, debugging, and test-driven development in cross-functional teams.
• Ability to obtain a SECRET clearance.

Preferences:

• Hands-on integration or algorithm development with airborne sensing systems.
• Experience with ML frameworks such as PyTorch or Tensorflow, particularly for vision-based object detection or classification tasks.
• Experience deploying perception software on SWaP-constrained platforms.
• Familiarity with validating perception systems during flight test events or operational environments.
• Understanding of sensing challenges in denied or degraded conditions.
• Exposure to perception applications across air, maritime, and ground platforms.

XML job scraping automation by YubHub

A successful candidate will be skilled in developing real-time object detection, sensor fusion, and state estimation algorithms using data from diverse mission sensors such as EO/IR cameras, radars, and IMUs. The role requires strong algorithmic thinking, deep familiarity with airborne sensing systems, and the ability to deliver performant software in simulation and real-world conditions.

We are seeking a skilled and motivated manager to lead technical teams and support direct projects integrating perception solutions for defense platforms.

Shield AI is committed to developing cutting-edge autonomy for unmanned aircraft operating across all Department of Defense (DoD) domains, including air, sea, and land. Our Perception Engineers are instrumental in creating the situational awareness that underpins autonomy, ensuring our systems understand and respond to the operational environment with speed, precision, and resilience.

Responsibilities:

• Multidisciplinary Team Leadership – Lead teams across autonomy, integration, and testing by aligning technical efforts, resolving cross-functional challenges, and driving mission-focused execution.
• Develop advanced perception algorithms , Design and implement robust algorithms for object detection, classification, and multi-target tracking across diverse sensor modalities.
• Implement sensor fusion frameworks , Integrate data from vision systems, radars, and other mission sensors using probabilistic and deterministic fusion techniques to generate accurate situational awareness.
• Develop state estimation capabilities , Design and refine algorithms for localization and pose estimation using IMU, GPS, vision, and other onboard sensing inputs to enable stable and accurate navigation.
• Analyze and utilize sensor ICDs , Interpret interface control documents (ICDs) and technical specifications for aircraft-mounted sensors to ensure correct data handling, interpretation, and synchronization.
• Optimize perception performance , Tune and evaluate perception pipelines for performance, robustness, and real-time efficiency in both simulation and real-world environments.
• Support autonomy integration , Work closely with autonomy, systems, and integration teams to interface perception outputs with planning, behaviors, and decision-making modules.
• Validate in simulated and operational settings , Leverage synthetic data, simulation environments, and field testing to validate algorithm accuracy and mission readiness.
• Collaborate with hardware and sensor teams , Ensure seamless integration of perception algorithms with onboard compute platforms and diverse sensor payloads.
• Drive innovation in airborne sensing , Contribute novel ideas and state-of-the-art techniques to advance real-time perception capabilities for unmanned aircraft operating in complex, GPS-denied, or contested environments.
• Travel Requirement , Members of this team typically travel around 10-15% of the year (to different office locations, customer sites, and flight integration events).

Required Qualifications:

• BS/MS in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, and/or similar degree, or equivalent practical experience
• Typically requires a minimum of 7 years of related experience with a Bachelor’s degree; or 5 years and a Master’s degree; or 4 years with a PhD; or equivalent work experience
• 5+ years of experience in Unmanned Systems programs in the DoD or applied R&D
• 2+ years of people leadership experience
• Background in implementing algorithms such as Kalman Filters, multi-target tracking, or deep learning-based detection models.
• Familiarity with fusing data from radar, EO/IR cameras, or other sensors using probabilistic or rule-based approaches.
• Familiarity with SLAM, visual-inertial odometry, or sensor-fused localization approaches in real-time applications.
• Ability to interpret and work with Interface Control Documents (ICDs) and hardware integration specs.
• Proficiency with version control, debugging, and test-driven development in cross-functional teams.
• Ability to obtain a SECRET clearance.

Preferred Qualifications:

• Hands-on integration or algorithm development with airborne sensing systems.
• Experience with ML frameworks such as PyTorch or Tensorflow, particularly for vision-based object detection or classification tasks.
• Experience deploying perception software on SWaP-constrained platforms.
• Familiarity with validating perception systems during flight test events or operational environments.
• Understanding of sensing challenges in denied or degraded conditions.
• Exposure to perception applications across air, maritime, and ground platforms.

XML job scraping automation by YubHub

A successful candidate will be skilled in developing real-time object detection, sensor fusion, and state estimation algorithms using data from diverse mission sensors such as EO/IR cameras, radars, and IMUs. The role requires strong algorithmic thinking, deep familiarity with airborne sensing systems, and the ability to deliver performant software in simulation and real-world conditions.

Develop advanced perception algorithms , Design and implement robust algorithms for object detection, classification, and multi-target tracking across diverse sensor modalities. Implement sensor fusion frameworks , Integrate data from vision systems, radars, and other mission sensors using probabilistic and deterministic fusion techniques to generate accurate situational awareness. Develop state estimation capabilities , Design and refine algorithms for localization and pose estimation using IMU, GPS, vision, and other onboard sensing inputs to enable stable and accurate navigation. Analyze and utilize sensor ICDs , Interpret interface control documents (ICDs) and technical specifications for aircraft-mounted sensors to ensure correct data handling, interpretation, and synchronization. Optimize perception performance , Tune and evaluate perception pipelines for performance, robustness, and real-time efficiency in both simulation and real-world environments. Support autonomy integration , Work closely with autonomy, systems, and integration teams to interface perception outputs with planning, behaviors, and decision-making modules. Validate in simulated and operational settings , Leverage synthetic data, simulation environments, and field testing to validate algorithm accuracy and mission readiness. Collaborate with hardware and sensor teams , Ensure seamless integration of perception algorithms with onboard compute platforms and diverse sensor payloads. Drive innovation in airborne sensing , Contribute novel ideas and state-of-the-art techniques to advance real-time perception capabilities for unmanned aircraft operating in complex, GPS-denied, or contested environments.

XML job scraping automation by YubHub

A successful candidate will be skilled in developing real-time object detection, sensor fusion, and state estimation algorithms using data from diverse mission sensors such as EO/IR cameras, radars, and IMUs. The role requires strong algorithmic thinking, deep familiarity with airborne sensing systems, and the ability to deliver performant software in simulation and real-world conditions.

Shield AI is committed to developing cutting-edge autonomy for unmanned aircraft operating across all Department of Defense (DoD) domains, including air, sea, and land. Our Perception Engineers are instrumental in creating the situational awareness that underpins autonomy, ensuring our systems understand and respond to the operational environment with speed, precision, and resilience.

Responsibilities:

• Develop advanced perception algorithms , Design and implement robust algorithms for object detection, classification, and multi-target tracking across diverse sensor modalities.
• Implement sensor fusion frameworks , Integrate data from vision systems, radars, and other mission sensors using probabilistic and deterministic fusion techniques to generate accurate situational awareness.
• Develop state estimation capabilities , Design and refine algorithms for localization and pose estimation using IMU, GPS, vision, and other onboard sensing inputs to enable stable and accurate navigation.
• Analyze and utilize sensor ICDs , Interpret interface control documents (ICDs) and technical specifications for aircraft-mounted sensors to ensure correct data handling, interpretation, and synchronization.
• Optimize perception performance , Tune and evaluate perception pipelines for performance, robustness, and real-time efficiency in both simulation and real-world environments.
• Support autonomy integration , Work closely with autonomy, systems, and integration teams to interface perception outputs with planning, behaviors, and decision-making modules.
• Validate in simulated and operational settings , Leverage synthetic data, simulation environments, and field testing to validate algorithm accuracy and mission readiness.
• Collaborate with hardware and sensor teams , Ensure seamless integration of perception algorithms with onboard compute platforms and diverse sensor payloads.
• Drive innovation in airborne sensing , Contribute novel ideas and state-of-the-art techniques to advance real-time perception capabilities for unmanned aircraft operating in complex, GPS-denied, or contested environments.
• Travel Requirement , Members of this team typically travel around 10-15% of the year (to different office locations, customer sites, and flight integration events).

Requirements:

• BS/MS in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, and/or similar degree, or equivalent practical experience
• Typically requires a minimum of 10 years of related experience with a Bachelor’s degree; or 9 years and a Master’s degree; or 7 years with a PhD; or equivalent work experience
• Background in implementing algorithms such as Kalman Filters, multi-target tracking, or deep learning-based detection models
• Familiarity with fusing data from radar, EO/IR cameras, or other sensors using probabilistic or rule-based approaches
• Familiarity with SLAM, visual-inertial odometry, or sensor-fused localization approaches in real-time applications
• Ability to interpret and work with Interface Control Documents (ICDs) and hardware integration specs
• Proficiency with version control, debugging, and test-driven development in cross-functional teams
• Ability to obtain a SECRET clearance

Preferences:

• Hands-on integration or algorithm development with airborne sensing systems
• Experience with ML frameworks such as PyTorch or Tensorflow, particularly for vision-based object detection or classification tasks
• Experience deploying perception software on SWaP-constrained platforms
• Familiarity with validating perception systems during flight test events or operational environments
• Understanding of sensing challenges in denied or degraded conditions
• Exposure to perception applications across air, maritime, and ground platforms

XML job scraping automation by YubHub

A successful candidate will be skilled in developing real-time object detection, sensor fusion, and state estimation algorithms using data from diverse mission sensors such as EO/IR cameras, radars, and IMUs. The role requires strong algorithmic thinking, deep familiarity with airborne sensing systems, and the ability to deliver performant software in simulation and real-world conditions.

Shield AI is committed to developing cutting-edge autonomy for unmanned aircraft operating across all Department of Defense (DoD) domains, including air, sea, and land. Our Perception Engineers are instrumental in creating the situational awareness that underpins autonomy, ensuring our systems understand and respond to the operational environment with speed, precision, and resilience.

Responsibilities:

• Develop advanced perception algorithms , Design and implement robust algorithms for object detection, classification, and multi-target tracking across diverse sensor modalities.
• Implement sensor fusion frameworks , Integrate data from vision systems, radars, and other mission sensors using probabilistic and deterministic fusion techniques to generate accurate situational awareness.
• Develop state estimation capabilities , Design and refine algorithms for localization and pose estimation using IMU, GPS, vision, and other onboard sensing inputs to enable stable and accurate navigation.
• Analyze and utilize sensor ICDs , Interpret interface control documents (ICDs) and technical specifications for aircraft-mounted sensors to ensure correct data handling, interpretation, and synchronization.
• Optimize perception performance , Tune and evaluate perception pipelines for performance, robustness, and real-time efficiency in both simulation and real-world environments.
• Support autonomy integration , Work closely with autonomy, systems, and integration teams to interface perception outputs with planning, behaviors, and decision-making modules.
• Validate in simulated and operational settings , Leverage synthetic data, simulation environments, and field testing to validate algorithm accuracy and mission readiness.
• Collaborate with hardware and sensor teams , Ensure seamless integration of perception algorithms with onboard compute platforms and diverse sensor payloads.
• Drive innovation in airborne sensing , Contribute novel ideas and state-of-the-art techniques to advance real-time perception capabilities for unmanned aircraft operating in complex, GPS-denied, or contested environments.
• Travel Requirement , Members of this team typically travel around 10-15% of the year (to different office locations, customer sites, and flight integration events).

Required Qualifications:

• BS/MS in Computer Science, Electrical Engineering, Mechanical Engineering, Aerospace Engineering, and/or similar degree, or equivalent practical experience
• Typically requires a minimum of 7 years of related experience with a Bachelor’s degree; or 5 years and a Master’s degree; or 4 years with a PhD; or equivalent work experience
• Background in implementing algorithms such as Kalman Filters, multi-target tracking, or deep learning-based detection models
• Familiarity with fusing data from radar, EO/IR cameras, or other sensors using probabilistic or rule-based approaches
• Familiarity with SLAM, visual-inertial odometry, or sensor-fused localization approaches in real-time applications
• Ability to interpret and work with Interface Control Documents (ICDs) and hardware integration specs
• Proficiency with version control, debugging, and test-driven development in cross-functional teams
• Ability to obtain a SECRET clearance

Preferred Qualifications:

• Hands-on integration or algorithm development with airborne sensing systems
• Experience with ML frameworks such as PyTorch or Tensorflow, particularly for vision-based object detection or classification tasks
• Experience deploying perception software on SWaP-constrained platforms
• Familiarity with validating perception systems during flight test events or operational environments
• Understanding of sensing challenges in denied or degraded conditions
• Exposure to perception applications across air, maritime, and ground platforms

$182,720 - $274,080 a year

XML job scraping automation by YubHub