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Day Vision Scientist Jobs (NOW HIRING)

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Day Vision Scientist information

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$50.5K

$111.3K

$137.5K

How much do day vision scientist jobs pay per year?

As of Sep 5, 2026, the average yearly pay for day vision scientist in the United States is $111,343.00, according to ZipRecruiter salary data. Most workers in this role earn between $94,500.00 and $137,000.00 per year, depending on experience, location, and employer.

What is the difference between Day Vision Scientist vs Optometrist?

AspectDay Vision ScientistOptometrist
Required CredentialsAdvanced degrees in vision science or related fields, research experienceDoctor of Optometry (OD) license, clinical training
Work EnvironmentResearch labs, academic institutions, industry settingsPrivate practices, clinics, healthcare facilities
Industry UsageResearch, product development, academiaPatient eye care, diagnosis, treatment

Day Vision Scientists focus on research and development related to vision and visual processes, often working in labs or academic settings. Optometrists primarily provide clinical eye care, diagnosing and treating visual problems in patients. While both roles require knowledge of vision science, their work environments and responsibilities differ significantly.

What can you do with a day vision scientist degree?

A day vision scientist degree prepares individuals for research and clinical roles focused on understanding and improving visual function during daytime. Graduates can work in vision research laboratories, clinical settings, or industry, often utilizing skills in data analysis, optics, and visual testing. Certification or advanced training may enhance employment opportunities in specialized areas such as ophthalmology or optometry.

What does a day vision scientist do?

A day vision scientist researches how the visual system processes information, often conducting experiments and analyzing data related to visual perception, eye function, and related neurological processes. They typically work in laboratories or research settings, using tools like eye-tracking devices and imaging technology, and may collaborate with other scientists or clinicians to advance understanding of vision health.

What cities are hiring for Day Vision Scientist jobs?

Cities with the most Day Vision Scientist job openings:

What are the most commonly searched types of Vision Scientist jobs?

The most popular types of Vision Scientist jobs are:

What states have the most Day Vision Scientist jobs?

States with the most job openings for Day Vision Scientist jobs include:

Computer Vision / Deep Learning Scientist (Atlanta)

Aptonet

Atlanta, GA • On-site

Full-time

Posted 18 days ago


Key responsibilities

  • Design, develop, and implement computer vision algorithms and deep learning architectures for specialized use cases.

  • Own the model development lifecycle, including data evaluation, experimentation, validation, deployment, and post‑production support.

  • Collaborate with application development teams to integrate computer vision and deep learning models into existing applications and production environments.


Job description

Computer Vision / Deep Learning Scientist – SeniorPosition Overview

We are seeking a Senior Computer Vision / Deep Learning Scientist to design, develop, and deploy advanced computer vision and deep learning solutions for unique, high-impact applications. The successful candidate will combine strong theoretical knowledge with hands‑on industry experience to develop novel algorithms, custom deep learning architectures, and production‑ready machine learning solutions. This role will be a key contributor to a Digital Train Inspection project, applying computer vision and deep learning techniques to analyze visual data and support automated inspection capabilities.

The Senior Scientist will own the model development lifecycle from requirements gathering and data evaluation through model development, validation, production integration, and post‑production support. The role requires close collaboration with application development teams, business stakeholders, and senior leadership, as well as the ability to provide technical guidance to junior team members and lead targeted research initiatives.

Work Arrangement
  • Hybrid schedule: Two days onsite each week for candidates located in the Atlanta area.
  • Fully remote option available for candidates located outside the Atlanta area.
Key Responsibilities
  • Design, develop, and implement novel computer vision algorithms for specialized and unique use cases.
  • Design and build custom deep learning architectures tailored to specific business and technical requirements.
  • Develop and apply deep learning models for semantic segmentation, object detection, image classification, and related computer vision applications.
  • Evaluate model accuracy, robustness, quality, and performance, as well as the quality and suitability of underlying data sources.
  • Develop clean, scalable, maintainable, and production‑ready Python and machine learning code.
  • Partner with application development teams to integrate computer vision and deep learning models into existing applications and production environments.
  • Own the complete model development lifecycle, including requirements gathering, data assessment, experimentation, model development, validation, deployment, monitoring, and post‑production support.
  • Conduct research and experimentation to identify and implement new computer vision and deep learning techniques.
  • Communicate technical findings, model performance, research results, and recommendations clearly to colleagues, business partners, and senior management.
  • Provide technical guidance and mentorship to junior team members and oversee targeted research and team projects.
  • Contribute to hiring initiatives, including technical candidate evaluation, interviews, and assessment of prospective team members.
  • Collaborate across technical and business functions to translate complex computer vision challenges into practical, scalable solutions.
Required Qualifications
  • Bachelor’s, Master’s, or Ph.D. in Computer Science, Electrical Engineering, Machine Learning, Statistics, or a related technical field.
  • 1–3 years of relevant industry experience in a role such as Computer Vision Scientist, Data Scientist, Research Scientist, Machine Learning Scientist, or similar; 3+ years of experience is preferred. Candidates with equivalent proven qualifications may also be considered.
  • Excellent programming skills in Python, with demonstrated experience developing machine learning or deep learning solutions in an industry environment.
  • Hands‑on industry experience with PyTorch or another major deep learning framework.
  • Strong practical experience applying deep learning techniques to computer vision problems, including semantic segmentation, object detection, and image classification.
  • Ability to evaluate model performance and data quality and translate findings into actionable improvements.
  • Experience developing production‑ready machine learning solutions and collaborating with software/application development teams.
  • Strong analytical, problem‑solving, communication, and research skills.
Preferred Qualifications
  • 3+ years of professional experience in computer vision, machine learning, deep learning, or a closely related discipline.
  • Experience taking machine learning models from research or experimentation into production.
  • Experience working with large‑scale visual datasets and establishing data quality and model evaluation processes.
  • Experience mentoring technical professionals or leading research‑oriented projects.
  • Experience participating in technical recruiting, interviewing, or candidate evaluation.
Project Focus: Digital Train Inspection

The selected candidate will contribute to a Digital Train Inspection initiative, developing computer vision and deep learning capabilities that support automated analysis of train and rail‑related visual inspection data. The work will involve applying advanced image analysis and machine learning techniques to identify, classify, segment, and evaluate visual conditions relevant to inspection and maintenance workflows.

Core Technical Skills
  • Python
  • PyTorch or comparable deep learning frameworks
  • Computer Vision
  • Semantic Segmentation
  • Image Classification
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