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Entry Level Computer Vision Deep Learning Engineer Jobs in Nash, TX

Aspen Dental

Dental Assistant - Entry Level

Texarkana, TX · On-site

$15.50/hr

Paid time off and holidays, Health, Vision, and 401(k) savings plan * Free Continuing Education (CE ... Commitment to ongoing learning and professional development Aspen Dental-branded practices are ...

Jackson Hewitt COO

Entry-Level Tax Preparer

Atlanta, TX · On-site

Basic computer skills * Willingness to learn Additional Perks: * Full-time and part-time positions ... Low-cost benefits (healthcare, dental & vision) * Teladoc (Unlimited Teladoc sessions for you and ...

Albertsons

Front End Entry Level

Wake Village, TX · On-site

... learning opportunities! Whether you are here for your first job or your last, from groceries to ... Our vision is to be a retail leader admired for national strength with deep local roots, offering ...

New

Albertsons

Front End Entry Level

Wake Village, TX

... learning opportunities! Whether you are here for your first job or your last, from groceries to ... Our vision is to be a retail leader admired for national strength with deep local roots, offering ...

New

VIOC

Entry-level Lube Tech/Technician

Texarkana, TX · On-site

$15/hr

Medical, dental, and vision, plus prescription drug coverage with Health Savings Account ... All you need to do is bring your positive attitude, attention to detail, and passion for learning ...

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All JobsComputer Vision Deep Learning Engineer JobsEntry Level Computer Vision Deep Learning Engineer JobsEntry Level Computer Vision Deep Learning Engineer Jobs in Nash, TX

Entry Level Computer Vision Deep Learning Engineer information

See Nash, TX salary details

$43.8K

$109.6K

$124.1K

How much do entry level computer vision deep learning engineer jobs pay per year?

As of Sep 10, 2026, the average yearly pay for entry level computer vision deep learning engineer in Nash, TX is $109,649.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,600.00 and $118,700.00 per year, depending on experience, location, and employer.

What does an entry level computer vision deep learning engineer do?

An Entry Level Computer Vision Deep Learning Engineer works on developing and implementing algorithms that allow computers to interpret and understand visual information from the world, such as images or videos. They typically use deep learning techniques, especially neural networks, to build models for tasks like object detection, facial recognition, and image classification. Their responsibilities may include data preprocessing, model training and evaluation, writing code (often in Python), and collaborating with senior engineers on real-world projects. This role is ideal for those who have a strong foundation in machine learning, programming, and mathematics, but are just starting their careers in the field.

What types of projects do entry level computer vision deep learning engineers typically work on, and how is their work structured within a team?

As an entry-level Computer Vision Deep Learning Engineer, you can expect to contribute to projects like object detection, image classification, and model optimization for real-world applications. Your tasks may include data preprocessing, training and evaluating neural networks, and writing code to integrate models into products or pipelines. You'll often collaborate closely with senior engineers, data scientists, and product managers, typically working in agile teams where regular code reviews and knowledge sharing are common. This collaborative environment not only helps you learn best practices but also provides opportunities to gradually take on more responsibility as your skills develop.

What are the key skills and qualifications needed to thrive as an entry level computer vision deep learning engineer, and why are they important?

To thrive as an Entry Level Computer Vision Deep Learning Engineer, you need a solid understanding of computer vision fundamentals, deep learning concepts, and programming skills in languages like Python, along with a relevant degree in computer science, engineering, or a related field. Familiarity with frameworks such as TensorFlow or PyTorch, experience with OpenCV, and knowledge of version control systems like Git are typically required. Strong problem-solving abilities, attention to detail, and effective communication skills help you collaborate within teams and tackle complex challenges. These skills and qualities are crucial for developing, deploying, and optimizing computer vision solutions that meet real-world business needs.

What cities near Nash, TX are hiring for Entry Level Computer Vision Deep Learning Engineer jobs?

Cities near Nash, TX with the most Entry Level Computer Vision Deep Learning Engineer job openings:

Entry Level Computer Vision Deep Learning Engineer jobs near you
Infographic showing various Entry Level Computer Vision Deep Learning Engineer job openings in Nash, TX as of June 2026, with employment types broken down into 3% As Needed, 70% Full Time, 24% Part Time, and 3% Contract. Highlights an 96% Physical, 1% Hybrid, and 3% Remote job distribution, with an average salary of $109,649 per year, or $52.7 per hour.

Data Scientist (Statistician) - Direct Hire

Texarkana, AR • On-site

Criminal Investigation & Law Enforcement | IRS Careers
Public Administration • 10K+ employees
Learn more about Criminal Investigation & Law Enforcement | IRS Careersexternal

$125K/yr

Full-time

This job post has expired today. Applications are no longer accepted.

Internal Revenue Service rating

7.3

Company rating: 7.3 out of 10

Based on 131 frontline employees who took The Breakroom Quiz

Job description

WHAT IS LARGE BUSINESS AND INTERNATIONALDIVISION?
A description of the business units can be found at: https://www.jobs.irs.gov/about/who/business-divisions

  • Position is to be filled in the following area(s):
    • LBI - ADCCI - Assistant Deputy Commissioner Compliance Integration.


REVIEW THE ADDITIONAL INFORMATION BELOW FOR FURTHER DETAILS

Qualifications:Federal experience is not required. Experience may have been gained in the public sector, private sector or through Volunteer Service. One year of experience refers to full-time work; part-timework is considered on a prorated basis. To ensure full credit for your work experience, please indicate dates of employment by month/day/year, and indicate number of hours worked per week, on your resume.
You must meet the following requirements by the closing date of this announcement.
QUALIFICATION REQUIREMENTS: To qualify for this position, you must meet the qualification requirements outlined below:
BASIC REQUIREMENTS (IOR) ALL GRADES:
EDUCATION: A degree that included 15 semester hours in statistics (or in mathematics and statistics, provided at least 6 semester hours were in statistics), and 9 additional semester hours in one or more of the following: physical or biological sciences, medicine, education, or engineering; or in the social sciences including demography, history, economics, social welfare, geography, international relations, social or cultural anthropology, health sociology, political science, public administration, psychology, etc. Credit toward meeting statistical course requirements should be given for courses in which 50 percent of the course content appears to be statistical methods, e.g., courses that included studies in research methods in psychology or economics such as tests and measurements or business cycles, or courses in methods of processing mass statistical data such as tabulating methods or electronic data processing.
OR
COMBINATION OF EDUCATION AND EXPERIENCE: Combination of education and experience includes courses as shown in A above, plus appropriate experience or additional education. The experience should have included a full range of professional statistical work such as (a) sampling, (b) collecting, computing, and analyzing statistical data, and (c) applying statistical techniques such as measurement of central tendency, dispersion, skewness, sampling error, simple and multiple correlation, analysis of variance, and tests of significance.
AND
SPECIALIZED EXPERIENCE GS-14: In addition to meeting basic requirements, to be eligible for this position at this grade level, you must have one (1) year of specialized experience at a level of difficulty and responsibility equivalent to the GS-13 grade level in the Federal service.
Specialized experience for this position includes:
  • Experience identifying and assessing the validity and reliability of relevant data sources and retrieving structured and unstructured data in multiple types and formats, including Extensible Markup Language (XML) files and large datasets, for use in data science projects.
  • Experience cleaning, transforming, combining, and integrating structured and unstructured data from multiple sources, including identifying and resolving missing values, outliers, and duplicate records, to prepare data for analysis.
  • Experience applying data-mining process models, including the Cross-Industry Standard Process for Data Mining (CRISP-DM) or Sample, Explore, Modify, Model, Assess (SEMMA), to collect, prepare, analyze, and evaluate data during data science projects.
  • Experience applying statistical methods, probability, statistical inference, hypothesis testing, experimental design, forecasting, and sampling methods to analyze data, evaluate results, and support program or business decisions.
  • Experience developing and evaluating analytical and artificial intelligence models using machine learning, text analytics, natural language processing, large language models, graph theory, link analysis, optimization models, complex adaptive systems, or deep-learning neural networks.
  • Experience using programming languages, query languages, data-intelligence platforms, and data-storage technologies, including R, Python, Structured Query Language (SQL), Java, Databricks, Sybase, Oracle, or open-source databases, to retrieve, process, query, analyze, and integrate data during data science projects.
  • Experience planning, coordinating, monitoring, and evaluating data science projects; reviewing technical deliverables for validity and reliability; and communicating analytical findings, model results, limitations, conclusions, and recommendations to technical and nontechnical stakeholders through written products, presentations, graphs, tables, charts, or business-intelligence products.

AND
You must also meet the following requirements:
  • MINIMUM AGE REQUIREMENT: Minimum age for federal employment is 18 years old, or at least 16 years old and have:
    • Graduated from high school or been awarded a certificate equivalent to graduating from high school; or
    • Completed a formal vocational training program; or
    • Received a statement from school authorities agreeing with your preference for employment rather than continuing your education

For more information on qualifications please refer to OPM's Qualifications Standards.Education:A college or university degree generally must be from an accredited (or pre-accredited) college or university recognized by the U.S. Department of Education. For a list of schools which meet these criteria, please refer to Department of Education Accreditation page.
FOREIGN EDUCATION: Education completed in foreign colleges or universities may be used to meet the requirements. You must show proof the education credentials have been deemed to be at least equivalent to that gained in conventional U.S. education program. It is your responsibility to provide such evidence when applying. Click here (Section 3, Explanation of Terms) or here for Foreign Education Credentialing instructions.
We recommend choosing an evaluator from a member organization of one of the following national associations of credential evaluation services: National Association of Credential Evaluation Services (NACES) or Association of International Credentials Evaluators (AICE).Employment Type: OTHER

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