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Entry Level Deep Learning Jobs (NOW HIRING)

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Data Analyst

Duncan, OK

... Deep Learning packages for identifying data patterns and/or building predictive models Conduct ... Entry-Level Job Family: Engineering/Science/Technology Product Service Line: Production ...

IBM

NC · On-site

$14.25 - $18.75/hr

Experience with Machine Learning, Deep Learning, Large Language Models. * Experience with Generative AI and applications that use Text2SQL and Retrieval Augmented Generation (RAG). * Experience with ...

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Entry Level Deep Learning information

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$20.5K

$89.2K

$196.5K

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

As of Sep 10, 2026, the average yearly pay for entry level deep learning in the United States is $89,171.00, according to ZipRecruiter salary data. Most workers in this role earn between $38,000.00 and $148,500.00 per year, depending on experience, location, and employer.

What are entry level deep learning jobs?

Entry level deep learning jobs are positions designed for individuals who are new to the field of artificial intelligence and machine learning, typically recent graduates or those with limited professional experience. These roles often involve assisting in building, training, and testing neural network models, as well as preprocessing data and supporting senior data scientists or machine learning engineers. Entry level positions may also include tasks such as researching recent advancements, implementing standard algorithms, and contributing to team projects under supervision. A strong foundation in Python, deep learning frameworks like TensorFlow or PyTorch, and an understanding of basic machine learning concepts are usually required.

What are the key skills and qualifications needed to thrive as an entry level deep learning professional?

To thrive as an Entry Level Deep Learning professional, you need a solid understanding of machine learning fundamentals, mathematics (especially linear algebra and calculus), and proficiency in programming languages such as Python. Experience with frameworks like TensorFlow or PyTorch and familiarity with version control systems like Git are typically required. Strong problem-solving abilities, eagerness to learn, and the ability to work collaboratively set candidates apart in this field. These skills and qualities are essential for building, troubleshooting, and improving deep learning models in a rapidly evolving technical landscape.

What are some common challenges faced by entry level deep learning professionals, and how can they be addressed?

Entry-level deep learning professionals often encounter challenges such as understanding complex architectures, managing large datasets, and optimizing model performance. Navigating unfamiliar frameworks and debugging code can also be daunting at first. These challenges can be addressed by seeking mentorship from experienced colleagues, participating in code reviews, and dedicating time to hands-on projects. Additionally, staying updated with the latest research and utilizing online communities or forums can provide valuable support and resources.

What is the difference between Entry Level Deep Learning vs Entry Level Machine Learning?

AspectEntry Level Deep LearningEntry Level Machine Learning
Required CredentialsBachelor's in CS, Data Science, or related; familiarity with neural networksBachelor's in CS, Data Science, or related; basic understanding of algorithms
Work EnvironmentResearch labs, tech companies, AI startupsTech firms, finance, healthcare, and various industries
Employer & Industry UsageAI-focused roles, research institutionsBroader industry applications, including analytics and automation
Common Search & ComparisonOften compared for specialization in neural networks and deep architecturesMore general, covers broader ML techniques

Entry Level Deep Learning focuses on neural networks and complex models, often requiring knowledge of frameworks like TensorFlow or PyTorch. Entry Level Machine Learning covers a wider range of algorithms and techniques. Both roles share foundational skills but differ in specialization and application scope.

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What are the most commonly searched types of Deep Learning jobs?

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Entry Level Deep Learning jobs near you
Infographic showing various Entry Level Deep Learning job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 74% Full Time, 23% Part Time, and 1% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $89,171 per year, or $42.9 per hour.

Applied Researcher (San Francisco)

San Francisco, CA • On-site

Variant
Trucking • 501 - 1,000 employees
Learn more about Variantexternal

$300K/yr

Full-time

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

Job description

Join to apply for the Applied Researcher role at Variant

Overview

Variant is hiring an applied researcher to join our team in San Francisco. We are well-capitalized and focused on code generation with creativity and taste. This role involves designing, training, and evaluating deep neural networks and large language models (LLMs); prototyping quickly; turning promising ideas into reliable systems; collaborating with engineering and design; and communicating results clearly through papers, documentation, and crisp experiment reports.

Base pay range

$149,999.00/yr - $300,000.00/yr

Responsibilities
  • Design, train, and evaluate deep neural networks and LLMs
  • Own experiments end-to-end: hypotheses, datasets, metrics, results
  • Prototype fast; turn promising ideas into reliable systems
  • Collaborate with engineering and design to make ideas real
  • Write clearly: papers, docs, and crisp experiment reports
  • Don't compromise between rigor and shipping fast
  • See what needs to be done and do it
Minimum qualifications
  • 2+ years in PhD program or in industry
  • Experience training deep neural networks
  • Proficiency in frameworks like PyTorch
  • Published 1 or more papers in the subject of deep learning
Ideal qualifications
  • Experience training LLMs, including SFT, RL-based techniques, etc.
  • Experience in the domain of code generation
  • At least 1 paper accepted into a top conference
  • Proficiency in best software engineering practices
  • Repeated experience formulating, structuring, and answering open-ended questions
  • Passionate about visual design or UI design; prior work in the space

We’ve kept our team small by design. Your code will matter from day one, and its impact will compound over time. This will be the most meaningful work of your career. We work from a beautiful space in San Francisco where we dream up the future and make it real together. We’re well-capitalized and backed by notable investors. If you’ve built things you’re proud of, we’d love to see them.

Seniority level
  • Entry level
Employment type
  • Full-time
Job function
  • Research, Analyst, and Information Technology
Industries
  • Technology, Information and Internet

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