Neural Networks

Neural Networks Developer Jobs

2 jobs found

30d ago

Machine Learning Engineer

Escalon Santa Monica, CA

Santa Monica, CA

30d 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 help design and implement intelligent systems that extract meaning and predictive value from computer vision and behavioral datasets. The work centers on building models and embedding architectures that support future action prediction, semantic matching, and similarity-based inference, with training and deployment workflows built for real-world use.

This full-time, on-site role is based in Santa Monica, CA, with compensation of $100,000 to $120,000 per year. The position is intended for candidates with roughly 2–3 years of experience through internships, academic labs, or early career roles, and requires 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 or classification signals) into shared embedding spaces used for similarity and predictive tasks.
Build and fine-tune convolutional and transformer-based neural architectures focused on visual recognition and representation learning.
Develop encoding and embedding methods that enable 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 for behavioral inference and action prediction.
Support model training, evaluation, and deployment workflows, including data preprocessing, augmentation, hyperparameter tuning, and performance profiling.
Partner with teams 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.
2–3 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, or ResNet variants).
Experience training models using structured and unstructured visual datasets.
Exposure to techniques such as 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 for version control.
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 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

Work arrangement: On-site
Contract type: Full-time
Compensation: $100,000 to $120,000 per year
Eligibility: Must be a US Citizen or valid Green Card holder; visa sponsorship is not available.
Location requirement: Candidates must reside within a commutable distance of Santa Monica, California.

View full job page →

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

As a Machine Learning Engineer at Hive, you will prototype and productionize cutting edge neural network models, build scalable data pipelines, and collaborate with Backend and DevOps teams to deploy models in production.

Job Details

Location: San Francisco, CA (onsite)

Salary: USD 120,000 - 180,000 per year

Responsibilities

Design and implement neural network architectures and related code improvements
Source, curate, and refine training data
Train, tune, and optimize models for performance
Deploy models at scale with high throughput and availability
Evaluate live results to continuously improve accuracy and speed
Collaborate closely with Backend and DevOps teams and our internal data labeling services
Apply OWASP Top 10 security practices to protect code from vulnerabilities
Stay informed about industry best practices for data handling relevant to the role
Follow policies and procedures for safeguarding information assets
Report actual or suspected security or policy violations to the appropriate authority

Requirements

An undergraduate or graduate degree in computer science or a related technical field, with substantial coursework in mathematics or statistics
1 to 2 years of professional machine learning experience
Proven experience training and deploying a deep learning model (image, NLP, video, or audio) into production with measurable performance gains over a baseline
Strong experience with high level ML frameworks such as TensorFlow, Caffe, or Torch, with familiarity across the others
Proficient in Python and its use within the ML frameworks above
Able to rapidly prototype data pipelines using Python, Node, Bash, and Linux command-line tools, especially for large datasets containing millions of files
Working knowledge of C++, Scala/Spark, SQL, Cassandra, and Docker, with willingness to learn new technologies on the fly
Up to date with the latest deep neural net research and architectures, including theory, motivations, and practical implementation
Excellent communication and collaboration skills
Strong team player with a proactive, can-do attitude

Technologies

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

Benefits

Stock options may be offered

Who We Are

Hive is a forward looking AI startup based in San Francisco, built by a team of ambitious engineers focused on creating a revolutionary platform. The role presents a steep learning curve and the opportunity to contribute to a rapidly growing company with a tangible impact on product development.

View full job page →

Neural Networks Developer Jobs

Machine Learning Engineer

Machine Learning Engineer

Get Neural Networks Developer Jobs alerts