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New Grad Machine Learning Jobs in Perris, CA (NOW HIRING)

Sorenson Engineering

Machine Technician I/II

Yucaipa, CA · On-site

$20.75 - $26.75/hr

We thrive in a culture of innovation, attracting exceptional individuals who continually seek new ... Level I Basic-level position learning to follow procedures for operation of machines and inspection ...

New-Indy Containerboard

Scheduling Coordinator

Ontario, CA · On-site

$31 - $38/hr

Develop and manage production schedules that optimize machine capacity, manpower allocation, and ... Support production trials, new product introductions, and continuous improvement projects. * Assist ...

THE NEW-INDY GROUP

Scheduling Coordinator

Ontario, CA · On-site

$31 - $38/hr

Develop and manage production schedules that optimize machine capacity, manpower allocation, and ... Support production trials, new product introductions, and continuous improvement projects. * Assist ...

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All JobsNew Grad Machine Learning JobsNew Grad Machine Learning Jobs in Perris, CA

New Grad Machine Learning information

See Perris, CA salary details

$26K

$43.4K

$89.7K

How much do new grad machine learning jobs pay per year?

As of Sep 8, 2026, the average yearly pay for new grad machine learning in Perris, CA is $43,418.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,100.00 and $46,900.00 per year, depending on experience, location, and employer.

What is a new grad machine learning?

New Grad Machine Learning roles are entry-level positions designed for recent graduates who have studied machine learning, artificial intelligence, data science, or related fields. These positions typically involve working with experienced data scientists and engineers to develop, implement, and improve machine learning models and algorithms. New grads in these roles often contribute to projects involving data preprocessing, model training, evaluation, and deployment. The goal is to help new graduates gain hands-on experience and grow their skills in a real-world setting while contributing to the organization's AI initiatives.

What skills and qualifications are needed to thrive as a new grad machine learning?

To thrive as a New Grad Machine Learning Engineer, you need a solid foundation in mathematics, statistics, and programming (especially Python), typically supported by a degree in computer science or a related field. Familiarity with machine learning frameworks such as TensorFlow or PyTorch, version control systems like Git, and coursework or certification in data science are highly beneficial. Strong problem-solving abilities, curiosity, and effective communication skills help you collaborate and convey complex technical concepts to diverse teams. These skills and qualities are essential for developing innovative models, ensuring project success, and integrating seamlessly into fast-paced tech environments.

What challenges do new graduates face when starting out in a machine learning role, and how can they overcome them?

New grad machine learning engineers often encounter challenges such as bridging the gap between academic knowledge and practical, production-level projects. Adapting to real-world data issues, collaborating with cross-functional teams, and understanding scalable deployment can be daunting at first. To overcome these, it's helpful to seek mentorship, proactively ask questions, and dedicate time to learning best practices in code versioning, model evaluation, and team communication. Engaging in code reviews and participating in team discussions can also accelerate the learning curve and foster professional growth.

What is the difference between New Grad Machine Learning vs Data Scientist?

AspectNew Grad Machine LearningData Scientist
Required CredentialsBachelor's in CS, Data Science, or related field; some internshipsBachelor's or Master's in CS, Statistics, or related; some experience
Work EnvironmentEntry-level, team-focused, research and developmentData analysis, modeling, cross-functional collaboration
Employer & Industry UsageTech companies, startups, research labsTech, finance, healthcare, consulting firms

New Grad Machine Learning roles typically focus on foundational skills, internships, and entry-level tasks, while Data Scientist positions often require more experience in data analysis and statistical modeling. Both roles are common in tech industries, but Data Scientists usually handle broader data analysis responsibilities.

What cities near Perris, CA are hiring for New Grad Machine Learning jobs?

Cities near Perris, CA with the most New Grad Machine Learning job openings:

New Grad Machine Learning jobs near you

Computer Vision Engineer

Applied Medical

Rancho Santa Margarita, CA • On-site

$80K - $140K/yr

Full-time

Life, Retirement, PTO

Re-posted 7 days ago

Applied Medical rating

8.0

Company rating: 8.0 out of 10

Based on 23 frontline employees who took The Breakroom Quiz

Job description

Applied Medical is a new generation medical device company with a proven business model and commitment to innovation fueled by rapid business growth and expansion. Our company has been developing and manufacturing advanced surgical technologies for over 35 years and has earned a strong reputation for excellence in the healthcare field.  Our unique business model, combined with our dedication to delivering the highest quality products, enables team members to contribute in a larger capacity than is possible in typical positions.


Position Description

The Computer Vision Engineer develops and optimizes computer vision algorithms and deep learning models for image and video analysis at Applied Medical. This computer vision and machine learning engineering role integrates and deploys scalable, high-performance vision-based solutions into real-world products. The Computer Vision Engineer enhances model accuracy, improves system efficiency, and contributes to AI-driven products that advance computer vision technology across Applied Medical.

Key Responsibilities

  • Design, develop, and implement computer vision algorithms for object detection, segmentation, tracking, and feature extraction in image and video analysis
  • Collaborate with cross-functional teams to deploy and embed computer vision capabilities into products, including the Simsei simulation program
  • Optimize the accuracy, efficiency, and scalability of existing computer vision systems for real-world applications
  • Research emerging computer vision technologies and methodologies, applying insights to improve model performance
  • Test, validate, and deploy models, maintaining robustness and reliability in production environments
  • Monitor and troubleshoot deployed systems, resolving performance issues and implementing enhancements over time

Success in This Role Looks Like

  • Improving model accuracy and system efficiency across deployed computer vision solutions
  • Delivering scalable vision-based features integrated cleanly into production products
  • Maintaining robust, reliable models in production environments
  • Resolving performance issues quickly to sustain accuracy and efficiency
  • Applying current research to advance product capabilities and innovation

Position Requirements

This position requires the following skills and attributes:

  • Bachelor's degree in computer science, computer engineering, electrical engineering, or a related engineering field with an emphasis on computer vision, or relevant experience
  • Minimum of three years of relevant work experience, or equivalent education and experience demonstrating the skills below
  • Strong analytical skills and a solid foundation in mathematics
  • Deep understanding of and hands-on experience with image processing, computer vision, machine learning, and deep learning algorithms
  • Strong development skills in C++ or Python
  • Experience applying traditional computer vision and deep learning algorithms to problems such as object detection, segmentation, tracking, and feature extraction
  • Experience with data science and computer vision libraries, including NumPy, Pandas, SciPy, Matplotlib, Scikit-learn, and OpenCV
  • Experience with deep learning frameworks such as PyTorch, TensorFlow, or Keras

Preferred

The following skills and attributes are preferred:

  • Experience with medical image analysis or medical applications
  • Experience with image streaming and real-time image analysis
  • Experience with computer graphics and visualization
  • Experience with database servers such as MySQL or SQL Server
  • Experience with cloud services such as Amazon Web Services (AWS), Azure, or Google Cloud Platform (GCP)

Benefits
  • Competitive compensation range: $80000 - $140000 / year (California).  
  • Comprehensive benefits package.  
  • Training and mentorship opportunities.  
  • On-campus wellness activities.  
  • Education reimbursement program.  
  • 401(k) program with discretionary employer match.  
  • Generous vacation accrual and paid holiday schedule.  

Please note that the compensation range may be adjusted in the future, and bonus and incentive compensation plans may apply.  

Our total reward package reflects our commitment to employee growth and well-being, as we invest in your development and offer a range of benefits designed to enhance your career and life.  

All compensation and benefits are subject to plan documents and written agreements.  

Qualifications:

This position requires the following skills and attributes:

  • Bachelor's degree in computer science, computer engineering, electrical engineering, or a related engineering field with an emphasis on computer vision, or relevant experience
  • Minimum of three years of relevant work experience, or equivalent education and experience demonstrating the skills below
  • Strong analytical skills and a solid foundation in mathematics
  • Deep understanding of and hands-on experience with image processing, computer vision, machine learning, and deep learning algorithms
  • Strong development skills in C++ or Python
  • Experience applying traditional computer vision and deep learning algorithms to problems such as object detection, segmentation, tracking, and feature extraction
  • Experience with data science and computer vision libraries, including NumPy, Pandas, SciPy, Matplotlib, Scikit-learn, and OpenCV
  • Experience with deep learning frameworks such as PyTorch, TensorFlow, or Keras
Education:UNAVAILABLEEmployment Type: FULL_TIME

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