1

Annotation Math Jobs in Simi Valley, CA (NOW HIRING)

Provide insights to data collection and annotation and collaborate with the data team for in-house ... MS degree in computer science, engineering, or mathematics * 2-3 years of relevant experience in ...

Provide insights to data collection and annotation and collaborate with the data team for in-house ... MS degree in computer science, engineering, or mathematics * 2-3 years of relevant experience in ...

Understand customer data pipelines, workflow dependencies, annotation processes, and training stack ... Technical degree in Computer Science, Engineering, Data Science, Mathematics, or related discipline

Annotation Math information

See Simi Valley, CA salary details

$23.2K

$60.7K

$97.6K

How much do annotation math jobs pay per year?

As of Jun 10, 2026, the average yearly pay for annotation math in Simi Valley, CA is $60,737.00, according to ZipRecruiter salary data. Most workers in this role earn between $46,500.00 and $72,300.00 per year, depending on experience, location, and employer.

What is the difference between Annotation Math vs Data Annotator?

AspectAnnotation MathData Annotator
Required CredentialsBasic education, sometimes specialized training in annotation toolsHigh school diploma or equivalent, on-the-job training
Work EnvironmentData labeling teams, tech companies, remote or onsiteData labeling teams, tech companies, remote or onsite
Industry UsageAI, machine learning, data scienceAI, machine learning, data science
Common Search IntentUnderstanding roles related to data annotation and mathComparing data annotation jobs

Annotation Math and Data Annotator roles both involve data labeling within AI and machine learning industries. Annotation Math may focus more on mathematical annotations, while Data Annotator generally covers broader data labeling tasks. Both roles often share similar work environments and required skills, making them closely related in the data annotation field.

What are Annotation Math jobs?

Annotation Math jobs involve labeling, tagging, and categorizing mathematical data, such as equations, formulas, graphs, or written math problems, to create high-quality datasets. These annotated datasets are often used to train artificial intelligence (AI) and machine learning models to recognize and process mathematical content accurately. Annotation Math professionals need a strong understanding of mathematics, attention to detail, and familiarity with annotation tools or platforms. This work is critical for improving technologies like automated math solvers, educational apps, and document digitization.

What are the key skills and qualifications needed to thrive as an Annotation Math Specialist, and why are they important?

To thrive as an Annotation Math Specialist, you need a solid understanding of mathematics, attention to detail, and familiarity with educational or assessment standards, often supported by a relevant degree. Proficiency with annotation tools, data labeling platforms, and sometimes LaTeX or similar mathematical typesetting systems is typically required. Strong analytical thinking, communication, and the ability to work independently are essential soft skills for accuracy and consistency. These skills and qualities are crucial to ensure high-quality, precise annotations that support machine learning, educational resources, or assessment development.

What are some common challenges faced by professionals in Annotation Math roles, and how can they be addressed?

Professionals in Annotation Math roles often encounter challenges such as interpreting ambiguous mathematical data, maintaining consistency in labeling complex equations, and managing repetitive tasks that require high attention to detail. Addressing these challenges involves following clear annotation guidelines, collaborating with team members to resolve uncertainties, and utilizing quality assurance tools to minimize errors. Regular feedback sessions and ongoing training also help ensure accuracy and support professional growth in this specialized field.
What job categories do people searching Annotation Math jobs in Simi Valley, CA look for? The top searched job categories for Annotation Math jobs in Simi Valley, CA are:
What cities near Simi Valley, CA are hiring for Annotation Math jobs? Cities near Simi Valley, CA with the most Annotation Math job openings:

AI/ML Engineer - Architectural Drawing Understanding (US)

Genia

Los Angeles, CA

Other

Posted 3 days ago


Job description

AI/ML Engineer – Architectural Drawing Understanding (US)

Los Angeles, CA, USA

Responsibilities

We are seeking an AI/ML Engineer with strong expertise in Computer Vision (CV) to build intelligent systems that can interpret architectural drawings in DWG format. The role emphasizes designing and training computer vision pipelines — from classical CV methods to state-of-the-art deep learning models — to extract geometry, text, symbols, and structural information from technical drawings. While CAD format familiarity is helpful, deep CV expertise is the primary requirement.

  • Develop and optimize computer vision models (classical + deep learning) for entity detection, segmentation, symbol recognition, and annotation extraction from architectural drawings.
  • Apply classical CV techniques (e.g., edge detection, contour analysis, Hough transform, morphological operations) alongside deep learning models to solve vector and raster understanding tasks.
  • Design and train deep learning models (e.g., CNNs, Mask R-CNN, U-Net, YOLO, DETR, Vision Transformers) for detection and segmentation of CAD drawing elements.
  • Implement OCR pipelines for text and dimension extraction in drawings.
  • Build robust data pipelines: preprocessing DWG files, rasterization/vectorization, augmentation, and dataset creation for supervised training.
  • Benchmark, evaluate, and continuously improve model accuracy, robustness, and efficiency.
  • Collaborate with cross-functional teams to integrate vision models into design automation and CAD/BIM workflows.
Qualifications

EDUCATION & BACKGROUND

  • Bachelor's, Master's, or PhD in Computer Science, Artificial Intelligence, Computer Vision, or related fields.
  • Strong foundation in mathematics, geometry, and image processing.

COMPUTER VISION EXPERTISE (PRIORITY)

  • 3+ years of hands-on experience building CV pipelines and production-ready ML models.
  • Proven track record with classical CV algorithms (OpenCV, scikit-image): contour/edge detection, shape matching, geometric transformations, Hough transform, morphological filtering.
  • Strong experience training and deploying deep learning CV models: CNNs, U-Net, Mask R-CNN, Faster R-CNN, YOLO, DETR, Vision Transformers, SAM, etc.
  • Experience with OCR (e.g., Tesseract, deep-learning-based text recognition).
  • Practical experience in combining classical CV with deep learning for hybrid solutions.

TECHNICAL SKILLS

  • Proficiency in Python and ML frameworks (PyTorch, TensorFlow).
  • Strong engineering practices: Git, CI/CD, testing, Docker, and scalable inference deployment.
  • Familiarity with vector graphics, CAD data formats (DWG/DXF), and computational geometry is a plus, but not mandatory.

PREFERRED SKILLS

  • Knowledge of geometric deep learning or graph-based approaches for structured vector data.
  • Experience with annotation tools, dataset creation, and augmentation for CV tasks.
  • Familiarity with AEC (Architecture, Engineering, Construction) workflows is an advantage.
About Us

Established in 2023, Genia is dedicated to empowering the North American real estate market with generative AI. Our product, Structural CoPilot, automates the generation of structural engineering design drawings for the construction sector, enhancing efficiency and quality for engineering design firms and real estate developers.

The founding team has a deep background in the architecture and AI industries, with experience from leading internet and architectural engineering companies such as Amazon, Tencent, and ARUP. Team members hold degrees from renowned universities, including Yale, UPenn, Columbia, CMU, Duke, UCLA, and UBC. They have a proven track record of building multiple AI products from the ground up.

In early 2024, Genia successfully closed a multi-million dollar financing round with investors including a top-tier Silicon Valley venture capital firm and Europe's largest construction technology fund. We have also established strategic partnerships with several North American architectural engineering firms. The company is in a phase of rapid expansion and offers a competitive compensation package, including equity incentives for outstanding talent. We sincerely invite talented individuals from all backgrounds to join us!