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AeroVironment

Defense technology and unmanned aerial systems

Lead Machine Learning Engineer

Computer VisionConfirmed live in the last 24 hours
Full-timeCentreville, VA, USA$158k - $241k

About the Job

Requirements

  • A bachelor's degree in computer science/engineering, Mathematics, Physics, or a related Science or Engineering discipline, with relevant experience in machine learning and/or computer vision.
  • A minimum of 10–12 years of relevant experience.
  • Familiarity with C/C++ or Python.
  • Demonstrated ability to design, implement, and troubleshoot complex systems.
  • Proficiency with a deep learning framework, preferably PyTorch.
  • Proficiency with basic machine learning libraries such as scikit-learn and pandas.
  • Proficiency with OpenCV.
  • Proficiency with Linux.
  • Familiarity with machine learning standards such as ONNX.
  • Ability to select hardware for specific machine learning applications.
  • Expertise in visualizing and manipulating big datasets.
  • Ability to work within defined requirements to complete tasks under minimal supervision.
  • Ability to work in an office environment.
  • Ability to sit and stand for long periods and to talk, hear, and use hands and fingers to operate a computer keyboard.
  • U.S. citizenship is required.
  • Active Secret-level DoD security clearance, with the ability to obtain TS/SCI clearance.
  • Willingness and ability to travel occasionally, up to 20%.

Responsibilities

  • Lead the design and development of computer vision and machine learning algorithms to address technically challenging problems, including detecting, classifying, localizing, and tracking objects of interest from stationary and mobile sensor platforms.
  • Maintain awareness of relevant academic literature, commercial products, and open-source projects to ensure technical solutions remain current.
  • Advise on and support the design of software infrastructure and DevOps processes to support machine learning needs.
  • Implement machine learning algorithms and validate designs through purpose-designed experiments.
  • Analyze machine learning algorithms and trained-model errors, and design strategies to address them.
  • Select appropriate datasets and data representations, and supervise data acquisition when required.
  • Manage available hardware, data, and personnel resources to meet deadlines, and coordinate the activities of others as team lead.
  • Interact with teams within and outside the LEAP group across the development cycle, including requirements definition, concept design, prototyping, detailed design, testing and evaluation, and validation and verification testing.

Desired Qualifications

  • Experience working with DoW and Intelligence Community organizations on advanced technology, research, or artificial intelligence/machine learning initiatives.
  • Familiarity with working in classified spaces.
  • Familiarity with office software and computer-based productivity tools.
  • Leadership qualities.
  • Problem-solving and analytical skills.
  • Interpersonal and communication skills.
  • Ability to work in a fast-paced, deadline-driven environment where small teams share a broad variety of duties.
  • Initiative and drive to accomplish goals and meet company objectives.
  • Ownership and responsibility for current and past work products.
  • Commitment to learning from mistakes and improving personal, team, and company performance.
  • Focus on teamwork and collaboration, putting the success of the team above one's own interests.

About the Company

AeroVironment

Defense technology and unmanned aerial systems

AeroVironment designs and builds robotic systems for defense across air, land, and space, including small reconnaissance drones, high-altitude aircraft, and loitering munitions. These products work by carrying sensors and control software that allow autonomous or semi-autonomous missions, with real-time data collection, and, for weapons-enabled models, a payload and deployment mechanism for precision strikes. The company differentiates itself through a growing, multi-domain defense portfolio built via acquisitions, creating an integrated platform that combines drones with space tech, counter-UAS, and other defense capabilities. Its goal is to become a comprehensive defense-technology provider that can win large, long-term contracts by offering coordinated, autonomous systems across multiple domains.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Crystal City, Virginia
Founded
1971

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