Convolutional Neural Networks

Convolutional Neural Networks Engineer Jobs

2 jobs found

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 in Santa Monica, CA to design and implement intelligent systems that extract predictive and semantic value from computer vision and behavioral datasets. The role centers on building models that learn shared representations from visual inputs, enabling tasks such as future action prediction, semantic matching, and similarity-based inference.

This is an on-site, full-time position for candidates with hands-on machine learning experience, working closely with engineers across computer vision, embedded systems, software, and UI/UX to integrate AI pipelines into real-time systems.

Key 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 techniques that support consistent comparison across multiple data types (including pose vectors, facial landmarks, and class labels).
Use methods such as cosine similarity, distance metrics, and latent clustering for behavioral inference and action prediction.
Support model training, evaluation, and deployment workflows, including data preprocessing and augmentation, hyperparameter tuning, and performance profiling.
Collaborate with engineers in computer vision, embedded systems, software, and UI/UX to ensure AI pipelines integrate smoothly into real-time systems.
Write clean, well-documented code, and maintain version-controlled model artifacts and experiment logs.
Create technical documentation covering models, training procedures, evaluation criteria, and system integration.

Required Qualifications

Bachelor’s or Master’s degree in Artificial Intelligence, Data Science, Computer Science, Machine Learning, or a closely related field.
2 to 3 years of machine learning experience 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, and ResNet variants).
Experience training models using 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 version control systems such as Git.
Collaborative mindset with excellent 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
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 blend image, pose, and metadata representations.
Familiarity with CLIP, DINO, or self-supervised representation learning.
Experience with MLOps or training orchestration tools such as MLflow, Weights & Biases, or DVC.

Additional Information

Location: Santa Monica, CA (on-site)
Contract type: Full-time
Compensation: USD 100,000 to 120,000 per year
Experience level: 1–2 years (as listed)
Must be a US Citizen or valid Green Card holder; visa sponsorship is not available.
Candidates must reside within commutable distance of Santa Monica, California.
Benefits include comprehensive health coverage and flexible PTO.

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1mo ago

Machine Learning Engineer II

Milwaukee Electric Tool Corporation Brookfield, WI

Brookfield, WI

1mo ago Closed

Full time Python AI Ai Ml

This position is no longer accepting applications (closed Sep 1, 2026).

Job Description

The Machine Learning Engineer II role focuses on designing, developing, and validating machine learning models for power tool solutions, collaborating with cross-functional teams to deploy ML features across Milwaukee products globally, and owning projects that require strong problem-solving, communication, and project-management skills. This onsite position is based in Brookfield, Wisconsin.

Responsibilities

Design, implement, and validate machine learning models tailored to power tool applications.
Collaborate with highly cross-functional teams to deliver solutions that enhance user outcomes.
Explore and evaluate new machine learning approaches for deployment within Milwaukee products worldwide, demonstrating strong problem-solving, critical thinking, and composure in a dynamic environment.
Communicate technical concepts effectively and exercise fundamental project management capabilities.
Exhibit proactive ownership of projects and tasks, with an understanding of their links to broader initiatives.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related field.
Completed coursework or specialization in Machine Learning and/or Data Science.
At least one year of hands-on experience applying machine learning principles and algorithms in contexts involving embedded systems, edge computing, signal processing, or related areas.
Proven experience applying fundamental machine learning algorithms in non-coursework settings, including unsupervised or supervised learning, classification/regression, dimensionality reduction, and model optimization.
Experience with machine learning and AI methods such as CNNs, transformers, or computer vision.
Proficiency in Python and debugging, with extensive use of libraries such as NumPy, pandas, scikit-learn, and Matplotlib.
Experience with at least one deep learning framework, such as PyTorch or TensorFlow.
Strong mathematical foundation in statistics, linear algebra, calculus, and optimization.
Experience using modern software development tools and version control systems.
Excellent problem-solving abilities, critical thinking, and capability to work under pressure in a dynamic environment.
Strong technical communication skills and fundamental project management abilities.
Demonstrated ownership of a project or tasks and understanding of their relationships to other initiatives.
Ability to travel up to 10 percent of the time, domestically and internationally.