Autonomy Engineer II

AeroVironment, Inc.; Moorpark (CA); On-site; USD 98,000 - 149,000; Full time

Job summary

AeroVironment, Inc. is seeking an Autonomy & Machine Learning Engineer II to join the R&D group. You will develop computer vision and ML solutions for defense and commercial UAV applications, spanning requirements, prototyping, and validation.

You will write and test code to integrate ML into aircraft systems, visualize data, and compare model performance across experiments. Strong software and hardware coordination is required.

Qualifications

• BDegree in a relevant field and equivalent experience.
• 2–5 years of relevant experience in ML/vision.
• Familiarity with C/C++ and MATLAB required.

Responsibilities

• Develop computer vision and ML algorithms for UAV payloads.
• Integrate ML models into aircraft autopilots and robotic systems.
• Analyze data, validate models, and optimize performance.
• Experimentally verify designs and measure effectiveness.
• Collaborate with R&D and cross-functional teams.

Skills

C/C++

MATLAB

Python

OpenCV

Linux

TensorFlow

Keras

scikit-learn

pandas

Data visualization

Education

BS in Computer Vision and Machine Learning

Tools

TensorFlow

Keras

OpenCV

Linux

Job description

Worker Type

Regular

Job Description

Job Description

Summary

The Autonomy & Machine Learning Engineer II will have the opportunity to interact with R&D Group to develop a variety of innovative computer vision detection, classification, localization, and tracking solutions for defense and commercial applications. These development efforts will generally be small focused design teams which will require a senior machine learning engineer to use a range of skills and tools across traditional engineering, computer science, and mathematical disciplines including computer vision, machine learning, optimization, deep convolutional neural networks, and visual tracking. This position will work on a variety of stages of development including requirements definition, concept design, prototyping, detailed design, test and evaluation and validation and verification testing.

Position Responsibilities

• Support development of computer vision and machine learning algorithms capable of detection, classifying, localizing, and tracking objects-of-interest from a group 1 UAV using the existing gimballed camera payload
• Write and test software to support the integration of machine learning algorithms into aircraft (such as autopilots, payloads, or other functional components) or other robotic systems.
• Explore and visualize data to gain an understanding of it, then identifying differences in data distribution that could affect
• Implement Machine Learning systems and validate designs through a series of purpose-designed experiments
• Create objectives and develop models that help to achieve them, along with metrics to track their progress
• Perform analysis tasks using AeroVironment and industry developed tools
• Managing available resources such as hardware, data, and personnel so that deadlines are met
• Analyze the ML algorithms to solve a given problem and ranking them by their success probability Performance when deploying the model in the real world; Verify data quality, and/or ensure it via data cleaning
• Analyze the errors of the model and designing strategies to overcome them
• Study and transform data science prototypes; Research and implement appropriate ML algorithms and tools
• Select appropriate datasets and data representation methods; Run machine learning tests and experiments
• Works on problems of moderate scope where analysis of situations or data requires a review of variety of factors. Exercises judgment within defined procedures and practices to determine appropriate action
• Other duties as assigned

Basic Qualifications (Required Skills & Experience)

• BS in Computer Vision and Machine Learning is required or equivalent combination of education, training, and experience - with qualifications in any of the following fields: Mathematics, Optimization, Computer Science/Engineering, Electrical Engineering, Aerospace, or Mechanical Engineering
• Minimum of 2 - 5 years' relevant experience
• Familiarity with C/C++ and Matlab required
• Familiarity with office software and computer-based productivity tools
• Demonstrated ability to troubleshoot complex systems

Other Matrixed Skills

• Proficiency with a deep learning framework such as TensorFlow or Keras
• Proficiency with Python and basic libraries for machine learning such as scikit-learn and pandas
• Expertise in visualizing and manipulating big datasets
• Proficiency with OpenCV
• Familiarity with Linux
• Ability to select hardware to run an ML model with the required latency
• Computational statistics
• Mathematical optimization
• Data mining
• Exploratory data analysis
• Predictive analytics

Other Qualifications & Desired Competencies

• Works well within defined requirements to complete tasks under moderate supervision
• Must be a team player and collaborate effectively
• Excellent verbal and written skills
• Has effective problem-solving, analytical and interpersonal skills
• Able to excel in a fast-paced, deadline-driven environment, where small teams share a broad variety of duties
• Displays strong initiative and drive to accomplish goals and meet company objectives
• Takes ownership and responsibility for current and past work products
• Is committed to learning from mistakes and driven to improve and enhance performance of oneself, others, and the company

Physical Demands

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

Clearance Level

No Clearance

The salary range for this role is:

$97,500 - $148,750

Salary Consideration

AeroVironment considers several factors when extending an offer, including but not limited to, the location, the role and associated responsibilities, a candidate's work experience, education/training, and key skills.

ITAR Requirement

This position requires access to information that is subject to compliance with the International Traffic Arms Regulations ("ITAR") and/or the Export Administration Regulations ("EAR"). In order to comply with t