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Entry Level Machine Learning Jobs in Redondo Beach, CA

SynergisticIT

Entry Level Data Scientiest

Los Angeles, CA · On-site

$18 - $24/hr

Machine Learning Algorithms - Linear Regression, Logistic Regression, Decision Tree * Unsupervised/Clustering algorithms * NLP models, Deep Learning models for image classification Desired Candidate ...

Long Wall

CNC Machinist

El Segundo, CA · On-site

$22 - $26/hr

CNC Machinist (Entry Level) Description We are looking for a Machine Shop Technician to support ... The Machine Shop Technician will be responsible for learning and executing manufacturing processes ...

Long Wall

CNC Machinist

El Segundo, CA

$22 - $26/hr

CNC Machinist (Entry Level) Description We are looking for a Machine Shop Technician to support ... The Machine Shop Technician will be responsible for learning and executing manufacturing processes ...

Long Wall

CNC Machinist

El Segundo, CA · On-site

$22 - $26/hr

CNC Machinist (Entry Level) Description We are looking for a Machine Shop Technician to support ... The Machine Shop Technician will be responsible for learning and executing manufacturing processes ...

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Entry Level Machine Learning information

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$12

$18

$22

How much do entry level machine learning jobs pay per hour?

As of Aug 12, 2026, the average hourly pay for entry level machine learning in Redondo Beach, CA is $18.50, according to ZipRecruiter salary data. Most workers in this role earn between $16.54 and $20.10 per hour, depending on experience, location, and employer.

What types of projects can an entry level machine learning professional expect to work on in their first year?

As an entry-level machine learning professional, you’ll typically start by supporting more senior data scientists and engineers with tasks such as data cleaning, exploratory data analysis, and building baseline models. You may work on pilot projects like developing recommendation systems, automating simple classification tasks, or contributing to model evaluation and performance tuning. Collaboration with cross-functional teams—including software engineers, product managers, and domain experts—is common, providing valuable exposure to real-world business problems and laying a foundation for more complex responsibilities as you gain experience.

How to get into entry level machine learning with no experience?

Entry level machine learning roles typically require foundational knowledge in programming, statistics, and data analysis. Gaining skills through online courses, practicing with projects, and learning tools like Python, TensorFlow, or scikit-learn can help build a portfolio; internships or entry-level positions can provide practical experience.

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

To thrive as an Entry Level Machine Learning Engineer, you need a solid background in mathematics, statistics, and programming (especially in Python), typically supported by a degree in computer science or a related field. Familiarity with machine learning frameworks like TensorFlow or PyTorch, version control systems like Git, and data analysis libraries is commonly required. Strong problem-solving abilities, curiosity, and effective communication skills help differentiate candidates in collaborative and fast-evolving environments. These skills and qualifications are essential for building, testing, and improving machine learning models that drive innovation and business value.

What is the difference between Entry Level Machine Learning vs Data Analyst?

AspectEntry Level Machine LearningData Analyst
Required CredentialsBachelor's in CS, Math, or related; some knowledge of programming and statisticsBachelor's in Statistics, Math, or related; proficiency in Excel, SQL, and data visualization tools
Work EnvironmentTech companies, startups, research labs; focus on developing models and algorithmsBusiness, finance, marketing; focus on interpreting data and generating reports
Employer & Industry UsageTech, e-commerce, healthcare; roles involve building predictive modelsRetail, finance, consulting; roles involve analyzing data trends and insights

Entry Level Machine Learning roles focus on developing algorithms and models using programming and statistical skills, often in tech-driven environments. Data Analysts interpret and visualize data to support business decisions, typically using tools like Excel and SQL. While both roles require analytical skills, Machine Learning positions emphasize coding and model development, whereas Data Analysts focus on data interpretation and reporting.

What are entry level machine learning jobs?

Entry-level machine learning jobs focus on creating and using software for the development of artificial intelligence (AI). In this role, you may help program computer software, engineer mechanical solutions, help develop learning objectives, and use analytics to determine whether or not the technology created is meeting development goals. Many entry-level machine learning jobs focus on particular parts of the industry. For example, some companies focus on surveillance and intelligence, while others are creating technology for self-driving vehicles. Employers often use this position as a type of extended learning period to help you develop your skills before you start taking responsibility for major projects.

More about Entry Level Machine Learning jobs
What are the most commonly searched types of Machine Learning jobs in Redondo Beach, CA? The most popular types of Machine Learning jobs in Redondo Beach, CA are:
What are popular job titles related to Entry Level Machine Learning jobs in Redondo Beach, CA? For Entry Level Machine Learning jobs in Redondo Beach, CA, the most frequently searched job titles are:
What cities near Redondo Beach, CA are hiring for Entry Level Machine Learning jobs? Cities near Redondo Beach, CA with the most Entry Level Machine Learning job openings:
Entry Level Machine Learning jobs near you
Infographic showing various Entry Level Machine Learning job openings in Redondo Beach, CA as of August 2026, with employment types broken down into 1% As Needed, 70% Full Time, 24% Part Time, 2% Temporary, and 3% Contract. Highlights an 87% Physical, 3% Hybrid, and 10% Remote job distribution, with an average salary of $38,470 per year, or $18.5 per hour.

Financial Analyst Internship - Fall 2026

Varda Space Industries

El Segundo, CA • On-site

Full-time, Internship

Re-posted 17 hours ago

Job description

About This Role 

Fall internships will range between the months of August and December. All dates dependent upon the university schedule of the selected students. Internships are full-time and on-site in Los Angeles, CA. To be considered for this internship, candidates must be actively enrolled in an accredited undergraduate or graduate degree program. 

Internships at Varda are optimal for students looking to grow technically and professionally while working on impactful projects critical to the company's success. You will be working on a collaborative team in a startup environment while being able to learn from some of most accomplished and experienced aerospace professionals in the world. We're dedicated to providing an experience that will let your decisions and contributions help drive Varda's success. 

As a part of the finance team you will collaborate with the team to develop data structures and enhance system capabilities for advanced analytics and dashboard creation. Utilize AI, Machine Learning, and LLMs to deliver business insights to executive leadership.

Responsibilities
  • Build data structure to support Business and Finance KPIs
  • Publish Dashboards to automate reporting
  • Review existing systems/tools and enhance reporting mechanisms
  • Enable Machine Learning to evolve automation
Basic Qualifications
  • Education: Currently enrolled in an undergraduate or postgraduate program, majoring in Computer Science or Computer Engineering. Preference for college juniors/rising seniors.
  • Programming Skills: Proficiency in Python, R, Java, Linux, C++, or VMWare.
  • AI/ML Knowledge: Strong understanding of Large Language Models (LLMs) and Machine Learning algorithms.
  • Framework Experience: Familiarity with machine learning frameworks and libraries such as TensorFlow, PyTorch, and scikit-learn.
Preferred Skills And Experience 
  • Project Experience: Previous involvement in AI/ML projects or internships.
  • Deep Learning: Knowledge of deep learning and neural networks.
  • Data Visualization: Experience with tools like Matplotlib and Seaborn.
  • Cloud Platforms: Familiarity with AWS, Google Cloud, or Azure.

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