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Entry Level Deep Learning Jobs in California (NOW HIRING)

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Entry Level Sales - Recent Grad

Long Beach, CA · On-site

$70K - $120K/yr

Throughout the program, you'll not only develop a deep understanding of the lending landscape ... Dedication to Learning: Embrace wholeheartedly a comprehensive training program tailored to ...

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All JobsDeep Learning JobsEntry Level Deep Learning JobsEntry Level Deep Learning Jobs in California

Entry Level Deep Learning information

See California salary details

$20.1K

$87.3K

$192.4K

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

As of Sep 6, 2026, the average yearly pay for entry level deep learning in California is $87,319.00, according to ZipRecruiter salary data. Most workers in this role earn between $37,210.00 and $145,415.00 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.

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

The most popular types of Deep Learning jobs in California are:

What are popular job titles related to Entry Level Deep Learning jobs in California?

For Entry Level Deep Learning jobs in California, the most frequently searched job titles are:

What job categories do people searching Entry Level Deep Learning jobs in California look for?

The top searched job categories for Entry Level Deep Learning jobs in California are:

Entry Level Deep Learning jobs near you
Infographic showing various Entry Level Deep Learning job openings in California as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $87,319 per year, or $42 per hour.

Entry-Level Structural Engineer | Designer

Degenkolb Engineers

San Francisco, CA

Full-time

Posted 19 days ago

Job description

Position Description

We review candidates for the Entry-Level Structural Engineer | Designer position on a rolling basis  throughout the year for offices in the United States including, Los Angeles, Oakland, Orange County, Sacramento, San Diego, San Francisco, California; Seattle, Washington; and Detroit and Grand Rapids, Michigan.

Launch your structural engineering career with meaningful work, trusted mentorship, and a team invested in your growth.

You may indicate interest in multiple locations on a single application; additional submissions are not necessary. Candidates are considered for one location at a time based on ranked preferences and office availability.

Who Thrives Here

You are a curious, collaborative graduating master's student who wants to understand not only how a solution works, but why it is right for the project. You may be especially interested in seismic analysis for our West Coast offices or steel design for our Michigan offices. You want more than a first job: you want meaningful technical challenges, access to experienced mentors, and a team that trusts you to learn, contribute, and grow.

At Degenkolb, early-career engineers are encouraged to ask thoughtful questions, understand the purpose behind the work, and connect technical decisions to clients, builders, users, and communities. You will be supported as you develop your voice, judgment, and confidence as an engineer.

Who We Are

Founded in 1940 and headquartered in San Francisco, Degenkolb Engineers helps make complex, high-stakes projects real. We bring deep technical expertise, disciplined creativity, and a practical understanding of construction to every challenge; building strong relationships early, making complexity easier to navigate, and keeping the success of projects central to our work.

Our teams deliver customized structural solutions across healthcare, education, science and technology, forensics, construction engineering, federal buildings, and other complex markets. Whether a project calls for navigating stringent codes, balancing budget and schedule, solving an unusual technical problem, or creating a landmark structural system, we connect the right people and ideas to develop solutions that serve our clients and communities.

Position Summary

As a Designer, you will contribute to the planning, analysis, and design of structural engineering projects alongside experienced engineers and project managers. Your work will include engineering analyses, contract documents, and project deliverables, with exposure to client collaborations, site visits, and multidisciplinary team delivery of construction projects.

This role provides a strong technical foundation through meaningful project work, mentorship, candid feedback, and purposeful professional development.

 What You'll Do
  • Structural Analysis & Design: Perform structural analysis and design tasks under the guidance of licensed engineers. Apply engineering principles and sound engineering judgment to develop safe, effective structural solutions and contract deliverables that meet the governing building codes.
  • Project Delivery & Quality: Produce accurate, organized, and high-quality work that reflects Degenkolb's standards. Build an understanding of project objectives, scope, budget, and schedule; manage assigned work; and communicate progress, questions, and potential issues early.
  • Client & Team Collaboration: Build trusted relationships with project teams and clients by participating in meetings, supporting client communications, preparing technical documentation, and communicating clearly and professionally in writing and conversation.
  • Project Site Experience: Participate in site visits with experienced engineers to observe existing conditions and construction activities, document field observations, and connect design decisions with how structures are built and perform in the real world.
  • Professional Growth & Development: Expand your technical knowledge and professional skills through project experience, mentorship, feedback, purposeful learning, challenging assignments, and participation in professional organizations while progressing toward PE licensure.
  • Ownership & Contribution: Take responsibility for your commitments, seek context when needed, share ideas, and contribute to the collective success of your project teams, office, and firm.

Minimum Requirements

  • Education: A master's degree in structural engineering is strongly preferred.
  • Alternative Path: Exceptional candidates with a bachelor's degree in civil engineering and one to two years of highly technical structural design experience will be considered if they demonstrate proficiency equivalent to advanced graduate-level work.
  • Core technical proficiency must be demonstrated through advanced graduate coursework or verified professional project experience in:

1.      Advanced steel design

2.  Advanced reinforced concrete design

3.      Advanced structural analysis

4.      Structural dynamics

5.      Earthquake engineering (West Coast offices)

  • Undergraduate GPA of 3.40 or higher; strong academic performance in graduate coursework is expected, where applicable
  • Unofficial undergraduate and graduate transcripts, as applicable
  • Professional written and verbal communication skills
  • Current authorization to work in the United States for any employer

Desired Qualifications

  • Passing score on the Fundamentals of Engineering (FE) exam
  • Additional coursework or experience in wood design, prestressed concrete, or finite element analysis, or
  • Additional coursework or experience in nonlinear analysis for West Coast office locations
  • Familiarity with engineering software and tools such as AutoCAD, Tekla, RISA, RAM, Revit, Excel, Mathcad, SAP2000, ETABS, Python, or similar platforms
  • Demonstrated leadership potential, initiative, and commitment to collaborative learning
  • Experience in seismic analysis and the design of buildings (West Coast offices)

Apply