Senior Machine Learning Engineer

AeroVironment is seeking a Senior Machine Learning Engineer to join the Learning and Active Perception (LEAP) group. In this Centreville, VA onsite role, you will develop computer vision and analytics capabilities that support defense and commercial applications, including real-time automated target recognition (ATR). Work spans the full development lifecycle from requirements through validation and verification testing.

What you’ll do

• Develop computer vision and machine learning algorithms for object detection, classification, localization, and tracking using stationary and mobile sensor platforms, with a focus on real-time automated target recognition (ATR)
• Conduct visual imagery data science to guide data collection, labeling, and selection for training deep computer vision models, then validate data selection and algorithm design using purpose-built experiments
• Evaluate machine learning approaches for a target problem and rank models by success probability on new data
• Define objectives, build models to meet them, and establish metrics to track progress
• Select datasets and data representations appropriate to the problem
• Analyze errors across data, models, and design strategies, then iterate to address them
• Write and test software that enables integration of machine learning algorithms into aircraft systems (including autopilots and payloads) or other systems
• Perform other duties as assigned

Required qualifications

• Bachelor’s degree in computer science/engineering, Mathematics, Physics, or a related Science or Engineering discipline, plus 5+ years of relevant experience in machine learning and/or computer vision
• 5 - 8 years of relevant computer vision experience
• Proficiency with Python and C/C++
• Proficiency with a deep learning framework, preferably PyTorch
• Proficiency with foundational computer vision and machine learning libraries such as Open-CV, scikit-learn, and pandas
• Familiarity with Linux
• Familiarity with Nvidia Tools (CUDA, JetPack, TensorRT) and experience with deployment processes to Nvidia Jetson processors and other Nvidia GPUs
• Demonstrated ability to troubleshoot complex systems and perform algorithmic optimization
• Ability to perform exploratory data analysis, including visualizing and manipulating large datasets
• Familiarity with office software and computer-based productivity tools
• Ability to work within defined requirements with minimal supervision
• Strong collaboration and teamwork skills
• Excellent verbal and written communication skills
• Strong problem-solving, analytical, interpersonal, and communication skills
• Ability to succeed in a fast-paced, deadline-driven environment with small teams and broad duties
• Strong initiative and drive to meet goals and company objectives
• Ownership of current and prior work products, including sharing results and providing feedback to teammates
• Commitment to learning from mistakes and improving performance of self, others, and the company
• U.S. Citizenship required
• Ability to obtain at minimum a Secret level DoD security clearance
• Willingness and ability to travel (Regularly / up to 40%)

Education

• Bachelor’s degree in computer science/engineering, Mathematics, Physics, or related Science or Engineering discipline
• Advanced degree preferred

Technologies

• Python, C/C++, PyTorch
• Open-CV, scikit-learn, pandas
• Linux
• CUDA, JetPack, TensorRT
• Nvidia Jetson, Nvidia GPUs
• Autopilots, payloads

Compensation and schedule

• Salary range: USD 129,500 - 197,500 per year
• Work schedule: 9/80
• Paid holiday shutdown

Benefits

• Medical, dental vision
• 401K with company matching

Location: Centreville, VA (onsite). Worker type: Regular. Clearance level: No Clearance. ITAR: U.S. Citizenship is required; Secret or Top Secret clearance, or the ability to obtain a clearance is desired.

Physical demands

• Ability to work in an office environment (Constant)
• Required to sit and stand for long periods; talk, hear, and use hands and fingers to operate a computer keyboard (Frequent)