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Lead Machine Learning Engineer

AeroVironment Centreville, VA

Centreville, VA

Today

$158k - $241k/yr Full time Manager Artificial Intelligence Automation

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Job Description

AeroVironment’s Learning and Active Perception (LEAP) group is building computer vision and related analytics for defense and commercial applications, and this Lead Machine Learning Engineer role helps drive that work from requirements through test, evaluation, validation, and verification. This position functions as a strong individual contributor and technical leader, with expectations to mentor more junior engineers and shape how solutions are designed, validated, and improved.

Role Overview

Serve as a technical leader in designing and delivering computer vision and machine learning algorithms for technically challenging detection, classification, localization, and tracking problems.
Work across a range of stationary and mobile sensor platforms.
Validate approaches through purpose-designed experiments and evaluate model performance by analyzing errors and developing strategies to overcome them.
Select datasets and data representations, including supervision of data acquisition when required.
Maintain technical awareness of relevant academic literature, commercial products, and open source projects to keep solutions current.

Responsibilities

Lead design and development of computer vision and ML algorithms for wide-ranging real-world problems.
Advise on and support software infrastructure and DevOps processes that enable ML needs.
Implement ML algorithms and validate designs through experiments.
Analyze trained model algorithms and errors; design strategies to address failure modes.
Manage resources including hardware, data, and personnel to meet deadlines and coordinate activities as needed with a Team Lead and across teams.
Maintain ownership and responsibility for current and past work products.
Perform other duties as assigned.

Required Qualifications

Bachelor’s degree in computer science/engineering, Mathematics, Physics, or a related Science or Engineering discipline, with 5+ years of relevant experience in machine learning and/or computer vision.
Minimum of 8-12 years of relevant experience.
Required 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 scikit-learn and pandas.
Proficiency with OpenCV.
Proficiency with Linux.
Familiarity with ML standards such as ONNX.
Ability to select hardware for specific ML applications.
Expertise in visualizing and manipulating big datasets.
Experience working with DoD and Intelligence Community (IC) organizations on advanced technology, research, or AI/ML initiatives.
Familiarity working in classified spaces.
U.S. Citizenship required.
Must be able to obtain at least a Secret level DoD security clearance.
Willingness to travel frequently (up to 40%).
Effective verbal and written communication, problem-solving, analytical, and interpersonal skills.
Ability to work within defined requirements with minimal supervision.
Leadership qualities, teamwork, collaboration, initiative, and ownership.
Must be able to work in an office environment; required to sit and stand for long periods and use a computer keyboard (frequent talking, hearing, and hand/finger use).
Has commitment to learning from mistakes and improving performance of self and others.

Technologies

C/C++, Python
PyTorch
scikit-learn, pandas
OpenCV
Linux
ONNX

Compensation and Location

Location: Centreville, VA (onsite)
Salary range: USD 158,000 - 241,000 per year

Benefits

Medical, dental, vision
401K with company matching
9/80 work schedule
Paid holiday shutdown

Compliance and ITAR

This position requires access to information subject to compliance with the International Traffic Arms Regulations (ITAR) and/or the Export Administration Regulations (EAR).

Clearance level: No Clearance.

Special requirements: Ability to obtain at minimum a Secret level DoD security clearance, U.S. Citizenship required, and willingness to travel frequently (up to 40%).

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1mo ago

Machine Learning Engineer

Escalon Santa Monica, CA

Santa Monica, CA

1mo ago Closed

$100k - $120k/yr Full time Artificial Intelligence Convolutional Neural Networks Deep Learning

This position is no longer accepting applications (closed Sep 5, 2026).

Job Description

Escalon is seeking a Machine Learning Engineer to design and implement intelligent systems that extract predictive signals and semantic meaning from computer vision and behavioral datasets. The role applies modern deep learning approaches to representation learning, enabling future action prediction, semantic matching, and similarity-based inference in real-world, real-time contexts.

This full-time, on-site position is based in Santa Monica, CA, with compensation listed at USD 100,000 to 120,000 per year. The position calls for 2 to 3 years of experience and a Bachelor's or Master's degree in a relevant field.

Responsibilities

Design and implement machine learning pipelines that encode visual inputs such as pose, face, and object/classification signals into shared embedding spaces for similarity and predictive tasks.
Build and fine-tune convolutional and transformer-based neural architectures for visual recognition and representation learning.
Develop encoding and embedding methods that support consistent comparison across multiple data types, including pose vectors, facial landmarks, and class labels.
Use techniques such as cosine similarity, distance metrics, and latent clustering to support behavioral inference and action prediction.
Support model training, evaluation, and deployment workflows, including data preprocessing, augmentation, hyperparameter tuning, and performance profiling.
Collaborate with engineers across computer vision, embedded systems, software, and UI/UX to integrate AI pipelines into real-time systems.
Produce clean, well-documented code and maintain version-controlled model artifacts and experiment logs.
Write technical documentation covering models, training procedures, evaluation criteria, and system integration.

Requirements

Bachelor's or Master's degree in Artificial Intelligence, Data Science, Computer Science, Machine Learning, or a closely related discipline.
2 to 3 years of experience in machine learning roles through internships, academic labs, or early career positions.
Strong understanding of Convolutional Neural Networks (CNNs) for image and video-based tasks.
Strong understanding of transformer architectures for vision or multimodal learning.
Strong understanding of embedding systems and vector space modeling for semantic and similarity-based tasks.
Strong understanding of encoding mechanisms and dimensionality reduction for latent representations.
Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow.
Familiarity with pose estimation, facial recognition, or classification models (for example: OpenPose, MediaPipe, FaceNet, ResNet variants).
Experience training with structured and unstructured visual datasets.
Exposure to cosine similarity, triplet loss, contrastive learning, or temporal prediction modeling.
Strong computer science fundamentals including data structures, algorithms, and software design patterns.
Comfort working in Linux-based development environments and using Git.
A collaborative mindset with strong communication skills and willingness to learn across domains.

Technologies

Python, PyTorch, TensorFlow
Git
OpenPose, MediaPipe, FaceNet, ResNet
ONNX, TensorRT
MLflow, Weights & Biases
DVC
CLIP, DINO

Benefits

Comprehensive health coverage
Flexible PTO
A collaborative and intellectually driven team environment
The opportunity to work on cutting-edge AI systems supporting mission-critical applications

Bonus (Nice-to-Have)

Experience integrating vision-based AI models into embedded or robotics systems
Familiarity with ONNX or TensorRT for model optimization and deployment
Background in sequence modeling, recurrent architectures, or video-based action recognition
Exposure to multimodal AI systems that combine image, pose, and metadata representations
Familiarity with techniques such as CLIP, DINO, or self-supervised representation learning
Experience with MLOps or training orchestration tools including MLflow, Weights & Biases, or DVC

Other Requirements

Must be a US Citizen or a valid Green Card holder. Visa sponsorship is not available for this role.
Candidates must reside within a commutable distance of Santa Monica, California.

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