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Neural Networks Data Jobs

3 jobs found

1d ago

Machine Learning Engineer

Escalon Santa Monica, CA

Santa Monica, CA

1d ago

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

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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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5d ago

Machine Learning Engineer

Hive San Francisco, CA

San Francisco, CA

5d ago

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

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Job Description

Responsibilities

Design and implement neural network models
Gather and refine data for model training
Train and tune models to achieve desired performance
Deploy models at scale with high throughput and uptime
Analyze production results and iteratively improve accuracy and speed
Work closely with Backend, DevOps, and internal data labeling services
Apply OWASP Top 10 security practices to secure code
Stay informed about industry best practices for data handling related to the role
Adhere to information protection policies and procedures
Report actual or suspected security or policy violations to the appropriate authority

Requirements

Bachelor’s or graduate degree in computer science or a similar 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) into production with measurable performance gains
Strong experience with high-level ML frameworks such as TensorFlow, Caffe, or Torch, with familiarity across others
Solid Python skills, particularly in the context of ML frameworks
Ability to quickly code and prototype data pipelines using Python, Node, Bash, and Linux CLI for large datasets
Working knowledge of C++, Scala/Spark, SQL, Cassandra, Docker or the ability to pick them up quickly
Up-to-date understanding of deep neural network research and architectures and how to implement them in your framework of choice
Strong communication skills and the ability to collaborate effectively
Proven team player with a do whatever it takes mindset

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 team of ambitious individuals focused on building a revolutionary AI company. The role offers a steep learning curve and the chance to contribute to one of San Francisco's fastest growing AI startups, with a tangible impact on the company's development. The stated base salary range for this position is USD 120,000 to 180,000 per year; actual compensation may vary based on qualifications, skills, competencies, experience, and location. Base pay is only part of the total compensation package, and stock options may be offered in addition to the range.

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17d ago

AI Data Scientist Senior Associate

PRICE WATERHOUSE COOPERS Boston, MA

Boston, MA

17d ago

$72k - $212k/yr Full time Senior Analytics Artificial Intelligence

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Job Description

Senior AI Data Scientist Associate at PwC in Boston, MA (onsite) leverages advanced analytics, statistical modeling, and machine learning to turn raw data into actionable insights for decision-making and business growth, with a salary range of USD 72,000 - 212,000 per year.

Responsibilities

Apply advanced analytics and statistical methods to extract insights from large datasets.
Design and deploy robust data solutions to convert raw data into actionable insights.
Perform exploratory and descriptive analyses to inform strategic decisions.
Utilize machine learning algorithms and predictive modeling to address complex business challenges.
Create data visualizations that clearly communicate insights and support data‑driven decisions.
Collaborate with clients to understand data needs and deliver tailored solutions.
Manage data pipelines and ensure data quality and integrity throughout the analysis process.
Implement data science workflows and troubleshooting techniques to optimize performance.
Commit to continuous learning to deepen technical skills and adapt to emerging technologies.
Mentor junior team members and foster a collaborative team environment.
Apply statistical analysis, machine learning, data preparation, experimentation, and model evaluation to develop and validate AI/ML solutions.
Use Python, data science libraries, model validation methods, and modern AI/ML approaches (including generative AI where relevant) to communicate actionable insights to business and technical stakeholders.
Demonstrate proficiency in data science algorithms and workflows.
Leverage machine learning and deep learning techniques effectively.
Excel in complex data analysis and predictive modeling.
Leverage experience with data engineering and data pipelines.
Apply knowledge of natural language processing and neural networks.
Navigate ambiguity while building meaningful client relationships.

Requirements

Bachelor’s degree required.
Minimum of 2 years of professional experience.

Technologies

Python
Generative AI
Neural networks
Natural language processing
Deep learning

Benefits

Annual discretionary bonus
Medical insurance
Dental insurance
Vision insurance
401k
Holiday pay
Vacation
Personal and family sick leave

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