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

Identify improvement areas and new market opportunities through firsthand exposure to semiconductor ... Strong understanding of leading image processing and machine learning libraries, including their ...

New

AI Engineer

Pleasanton, CA

$116K - $159K/yr

Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Data ... Evolving culture with the opportunity to drive new ideas and technology * Stock Option Grants

You'll combine deep data science expertise, hands-on machine learning experience, and an innovative ... Move beyond chatbots to create ambient, context-aware agents that boost efficiency and unlock new ...

You'll combine deep data science expertise, hands-on machine learning experience, and an innovative ... Move beyond chatbots to create ambient, context-aware agents that boost efficiency and unlock new ...

... discovering new advanced materials and chemicals. Work will focus on (1) the application of ... Prior experience with machine learning Engineering * Python (advanced) * Linux/RedHat/Bash ...

Head of Engineering

Walnut Creek, CA · On-site

$130K - $200K/yr

Ability to learn and apply new concepts rapidly * Extreme attention to details Plus * Familiarity ... Experience with machine learning Company Benefits Include * Health Care Plan (Medical, Dental ...

Showing results 41-60

New Grad Machine Learning information

See Tracy, CA salary details

$27.4K

$45.8K

$94.7K

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

As of Sep 15, 2026, the average yearly pay for new grad machine learning in Tracy, CA is $45,841.00, according to ZipRecruiter salary data. Most workers in this role earn between $35,000.00 and $49,500.00 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 Tracy, CA are hiring for New Grad Machine Learning jobs?

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

Infographic showing various New Grad Machine Learning job openings in Tracy, CA as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $45,841 per year, or $22 per hour.

Digital Analytics Solution Specialist

Dublin, CA • On-site

ZEISS
Scientific Research and Development Services

$190K - $237K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

Posted 3 days ago

New


ZEISS rating

7.5

Company rating: 7.5 out of 10

Based on 26 frontline employees who took The Breakroom Quiz


Job description

About Us:

How many companies can say they've been in business for over 179 years?!

Here at ZEISS, we certainly can! As the pioneers of science, ZEISS handles the everchanging environments in a fast-paced world, meeting it with cutting edge of technologies and continuous advancements. ZEISS believes that innovation and technology are the key to a sustainable future and solutions for global change. We have a diverse range of portfolios throughout the ZEISS family in segments like, Industrial Quality & Research, Medical Technology, Consumer Markets and Semiconductor Manufacturing Technology. We are a global company with over 42,000 employees and have over 4,000 in the US and Canada alone! Make a difference, come join the team!

What's the role?

The Semiconductor Fab Solutions (SFS) team within ZEISS SMT is seeking a customer-focused Digital Analytics Solution Specialist to help customers address complex semiconductor manufacturing challenges through data-driven application solutions. This role partners with key customers, segment leaders, scientists, and engineers to understand critical process needs, solve technical challenges, and drive adoption of innovative analytics tools that improve performance, decision-making, and business impact.

Sound Interesting?

Here's what you'll do:

  • Develop solution algorithms for semiconductor fabrication applications, using both classical image processing and state-of-the-art machine learning methods.

  • Build a strong understanding of semiconductor manufacturing processes, customer challenges, and market needs.

  • Define requirements from firsthand customer analytics needs and translate them into prototypes; develop, implement, test, and optimize solutions that address specific technical challenges.

  • Assess prototype capabilities and limitations, and clearly communicate findings to customers.

  • Work at customer and partner sites globally to gain firsthand experience and deeper insight into semiconductor industry needs.

  • Apply technical expertise and innovative thinking to deliver solutions that create meaningful impact for customers and the broader semiconductor industry.

  • Identify improvement areas and new market opportunities through firsthand exposure to semiconductor FIB-SEM applications at customer sites.

  • Develop customer-specific solutions through direct engagement at ZEISS customer sites.

  • Travel up to 50%, primarily within the United States, with occasional international support in locations such as Korea, Japan, China, Taiwan, and Germany.

Do you qualify?

  • Master's or PhD degree in computer science or a related field.

  • 1-2 years of experience designing and implementing machine learning algorithms for image processing applications, including neural networks for detection, classification, segmentation, and support vector machines.

  • Expertise in designing, analyzing, implementing, and testing image processing algorithms, including filters, noise and distortion correction, image registration and alignment, and contour extraction.

  • Ability to understand, maintain, and optimize existing code.

  • Strong understanding of leading image processing and machine learning libraries, including their strengths and limitations.

  • Background in semiconductor manufacturing preferred.

  • Experience working directly with customers in an interactive requirements-gathering environment.

Compensation

  • The annual pay range for this position is $190,000 - $237,000

  • The actual salary offered may vary based on factors such as job location, scope of the role, qualifications, education, experience, and the complexity, specialization, and scarcity of talent.

  • This position is also eligible for a performance bonus or sales commission, as applicable.

We have amazing benefits to support you as an employee at ZEISS!

  • Medical

  • Vision

  • Dental

  • 401k Matching

  • Employee Assistance Programs

  • Vacation and sick pay

  • The list goes on!

The above is intended to describe the general content of and requirements for this job. It is not to be construed as an exhaustive statement of requirements, duties, or responsibilities. The Company reserves the right to interpret, amend, or otherwise modify, in whole or in part, any job description at any time, at its sole discretion.

Your ZEISS Recruiting Team:

Maria Khalil

Zeiss provides Equal Employment Opportunity without unlawful regard to an Applicants race, color, religion, creed, sex, gender, marital status, age, national origin or ancestry, physical or mental disability, medical condition, military or veteran status, citizen status, sexual orientation, pregnancy (includes childbirth, breastfeeding or related medical condition), genetic predisposition, carrier status, gender expression or identity, including transgender identity, or any other class or characteristic protected by federal, state, or local law of the employee (or the people with whom the employee associates, including relatives and friends).


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