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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

Hive San Francisco, CA

San Francisco, CA

1mo ago Closed

$120k - $180k/yr Full time Python Artificial Intelligence Big Data

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

Job Description

$120,000 - $180,000 per year, with stock options potentially offered as part of the overall package.

Benefits

Stock options may be offered

Responsibilities

Design and implement neural network architectures and code
Collect, clean, and refine training data
Train, validate, and fine tune models
Deploy models at scale with high throughput and uptime
Monitor production results and iteratively improve accuracy and speed
Collaborate closely with Backend and DevOps teams as well as internal data labeling services
Apply OWASP top 10 security practices to keep code secure
Stay current with industry best practices for data handling and governance relevant to the role
Adhere to information protection policies and data handling guidelines
Report actual or suspected security or policy violations to the appropriate authority

Requirements

Undergraduate or graduate degree in computer science or a related technical field, with significant coursework in mathematics or statistics
1–2 years of industry machine learning experience
Proven track record of training and deploying a deep learning model (image, NLP, video, or audio) to production with measurable gains over a baseline
Strong experience with a high level ML framework such as TensorFlow, Caffe, or Torch, and familiarity with others
Proficiency in Python, applied to the above ML frameworks
Ability to quickly code and prototype data pipelines using Python, Node, Bash, and Linux command line tools, especially with large datasets
Working knowledge of C++, Scala/Spark, SQL, Cassandra, Docker, or willingness to learn quickly
Up to date on the latest deep neural net research and architectures and how to implement them in your ML framework of choice
Excellent communication and teamwork skills
Strong collaborative mindset and a can do attitude

Technologies

TensorFlow
Caffe
Torch
Python
Node
Bash
Linux command line tools
C++
Scala
Spark
SQL
Cassandra
Docker

Who we are

We are a group of ambitious individuals passionate about building a revolutionary AI company. At Hive you will encounter a steep learning curve and the opportunity to contribute to one of the fastest growing AI startups in San Francisco, with work that directly influences the company’s development. The base salary is in the range noted above, and compensation will reflect a candidate’s qualifications, skills, experience, and location; stock options may be offered in addition to base pay.

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