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Entry Level Google Machine Learning Engineer Jobs in California

Machine Learning Engineer II

Poway, CA · On-site

$98K - $171K/yr

We have an exciting opportunity for a Machine Learning Engineer in Poway, CA. The Autonomy and Artificial Intelligence Solutions Software group is charted to develop and deploy end-to-end autonomous ...

They are seeking a Machine Learning Engineer to train and deploy critical models for their core product, focusing on interpreting unstructured data and improving model performance. Responsibilities ...

Apple's Health Sensing team is seeking a versatile Machine Learning Engineer to develop next-generation health algorithms that deliver meaningful insights to users by combining classical ML, signal ...

We are looking for Machine Learning Engineers who have built product models from idea to delivery. You are passionate about digging into data, cleaning it, analyzing it, generating ideas, and ...

The Role We're looking for a Machine Learning Engineer who loves getting close to the metal. This is a hands-on engineering role focused on making models faster, more efficient, and more reliable ...

Machine Learning Engineer II

Palo Alto, CA · On-site

$114K - $156K/yr

Machine Learning Engineers (this role) who focus on modeling and algorithmic innovation * Machine Learning Infrastructure Engineers who build the platforms and tools that enable scalable training ...

Machine Learning Engineer II

Palo Alto, CA · On-site +1

$114K - $156K/yr

Machine Learning Engineers (this role) who focus on modeling and algorithmic innovation * Machine Learning Infrastructure Engineers who build the platforms and tools that enable scalable training ...

Machine Learning Engineer II

Palo Alto, CA · On-site +1

$145K - $165K/yr

Machine Learning Engineers (this role) who focus on modeling and algorithmic innovation * Machine Learning Infrastructure Engineers who build the platforms and tools that enable scalable training ...

Machine Learning Engineers (this role) who focus on modeling and algorithmic innovation * Machine Learning Infrastructure Engineers who build the platforms and tools that enable scalable training ...

... Google, AMD, Broadcom, Marvell, etc. We are a team of previous Stanford professors, SAIL ... Strong AI/ML engineering skills from top tier CS, EECS, Math and Physics programs. * Proven track ...

... Google, AMD, Broadcom, Marvell, etc. We are a team of previous Stanford professors, SAIL ... Strong AI/ML engineering skills from top tier CS, EECS, Math and Physics programs. * Proven track ...

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Entry Level Google Machine Learning Engineer information

What are Entry Level Google Machine Learning Engineers?

Entry Level Google Machine Learning Engineers are professionals who have recently started their careers in machine learning and work at Google. They typically assist in designing, developing, and deploying machine learning models to solve real-world problems. Their responsibilities may include data preprocessing, feature engineering, model training, evaluation, and collaborating with senior engineers and researchers. These roles often require a strong foundation in programming, mathematics, and statistics, as well as familiarity with machine learning frameworks such as TensorFlow or PyTorch. Entry Level Machine Learning Engineers at Google usually work on supervised projects and are mentored by more experienced team members.

What are the typical projects and responsibilities for an Entry Level Google Machine Learning Engineer?

As an Entry Level Machine Learning Engineer at Google, you can expect to work on a variety of projects ranging from building and optimizing machine learning models to supporting data preprocessing and feature engineering tasks. You will often collaborate with senior engineers, data scientists, and product teams to implement solutions that address real-world problems at scale. Your daily responsibilities may include coding in Python or TensorFlow, participating in code reviews, and troubleshooting model performance. This role offers hands-on experience with industry-leading tools and the opportunity to learn from experienced colleagues, making it a great foundation for career growth in AI and machine learning.

What is the difference between Entry Level Google Machine Learning Engineer vs Entry Level Data Scientist?

AspectEntry Level Google Machine Learning EngineerEntry Level Data Scientist
Required CredentialsBachelor's in CS, Math, or related; knowledge of ML frameworksBachelor's in CS, Stats, or related; strong analytical skills
Work EnvironmentDeveloping ML models, deploying algorithms, coding in Python/JavaData analysis, statistical modeling, data visualization
Employer & Industry UsageTech companies, especially Google, focusing on AI/ML productsVarious industries including tech, finance, healthcare

Entry Level Google Machine Learning Engineers focus on developing and deploying machine learning models, often requiring coding and understanding of ML frameworks. Entry Level Data Scientists analyze data, build statistical models, and create visualizations. While both roles require similar educational backgrounds, their daily tasks and focus areas differ, with ML Engineers more involved in algorithm implementation and Data Scientists in data analysis and insights.

What are the key skills and qualifications needed to thrive as an Entry Level Google Machine Learning Engineer, and why are they important?

To thrive as an Entry Level Google Machine Learning Engineer, you need a solid foundation in computer science, statistics, and mathematics, typically with at least a bachelor's degree in a related field. Familiarity with programming languages like Python or Java, experience using TensorFlow or PyTorch, and understanding of cloud platforms such as Google Cloud are essential technical requirements. Strong problem-solving skills, teamwork, and effective communication help you collaborate and convey complex concepts clearly. These skills and qualities are crucial for building scalable machine learning solutions and contributing effectively in a dynamic, innovative environment.
What are the most commonly searched types of Google Machine Learning Engineer jobs in California? The most popular types of Google Machine Learning Engineer jobs in California are:
What are popular job titles related to Entry Level Google Machine Learning Engineer jobs in California? For Entry Level Google Machine Learning Engineer jobs in California, the most frequently searched job titles are:
What job categories do people searching Entry Level Google Machine Learning Engineer jobs in California look for? The top searched job categories for Entry Level Google Machine Learning Engineer jobs in California are:
What cities in California are hiring for Entry Level Google Machine Learning Engineer jobs? Cities in California with the most Entry Level Google Machine Learning Engineer job openings:
Infographic showing various Entry Level Google Machine Learning Engineer job openings in California as of July 2026, with employment types broken down into 1% Locum Tenens, 91% Full Time, 4% Part Time, 1% Temporary, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution.
Machine Learning Engineer II

Machine Learning Engineer II

General Atomics

Poway, CA • On-site

$98K - $171K/yr

Full-time

Posted 28 days ago


General Atomics rating

8.9

Company rating: 8.9 out of 10

Based on 36 frontline employees who took The Breakroom Quiz

4th of 61 rated aerospace companies


Job description

Job Summary
General Atomics Aeronautical Systems, Inc. (GA-ASI), an affiliate of General Atomics, is a world leader in proven, reliable remotely piloted aircraft and tactical reconnaissance radars, as well as advanced high-resolution surveillance systems.
We have an exciting opportunity for a Machine Learning Engineer in Poway, CA. The Autonomy and Artificial Intelligence Solutions Software group is charted to develop and deploy end-to-end autonomous systems that enable unmanned aerial systems (UAS) to execute autonomous missions.
DUTIES AND RESPONSIBILITIES:
  • Develops and communicates descriptive, diagnostic, predictive and prescriptive insights/algorithms of limited scope.
  • In product/systems improvement projects, uses machine language and statistical modeling techniques to include but not limited to decision trees, logistic regression, Bayesian analysis and others to develop and evaluate algorithms to improve product/system performance, quality, data management and accuracy.
  • In both theoretical development environments and specific product design, implementation and improvement environments, uses programming language and technologies to translate algorithms and technical specifications into code.
  • Completes programming and implements efficiencies, performs testing and debugging.
  • Completes documentation and procedures for installation and maintenance.
  • Applies deep learning technologies to give computers the capability to visualize, learn and respond to situations of limited scope.
  • Lead technical teams and scope challenging projects into executable sprints.
  • Drive code reviews to help team adhere to general DevSecOps and MLOps best practices.
  • Have a growth mindset and be comfortable in a setting where milestones shift often due to customer preferences or technology evolution.
  • Adapts machine learning to areas such as virtual reality, augmented reality, artificial intelligence, robotics and other products that allow users to have an interactive experience.
  • Interface with external vendors and partners to integrate their technology into the team's autonomy stack.
  • Maintains the strict confidentiality of sensitive information.
  • Performs other duties as assigned.
  • Responsible for observing all laws, regulations and other applicable obligations wherever and whenever business is conducted on behalf of the Company. Expected to work in a safe manner in accordance with established operating procedures and practices.
We recognize and appreciate the value and contributions of individuals with diverse backgrounds and experiences and welcome all qualified individuals to apply.
Job Qualifications
  • Typically requires a bachelors or master's degree in computer science, engineering, mathematics, or a related technical discipline from an accredited institution and two or more years of machine learning experience with a bachelors degree. May substitute equivalent machine learning engineer experience in lieu of education.
  • Must have an understanding of machine learning concepts, principles, and theory.
  • Demonstrates the ability to follow and apply advanced machine learning knowledge, adapt cutting edge standard techniques, and utilize the required diagnostics, tools and equipment, while ensuring safety and regulatory compliance.
  • Experience in developing and leading scalable software architectures from scratch.
  • Experience in optimizing AI models to meet edge processing requirements.
  • Strong coding skills in Java, Java Script, C/C++, Python
  • Experience in AI frameworks such as Tensorflow and pyTorch.
  • Excellent verbal and written communication skills.
  • Must be able to architect, design, and develop complex software.
  • Technical expertise in the application of engineering principles, concepts, theory, and practice as well as project management and leadership skills including organizing, planning, scheduling, and coordinating workloads to meet established deadlines or milestones.
  • Active membership and participation in relevant conference and professional society organizations.
  • Demonstrated recent history of academic quality publications in the area of AI/ML and autonomy.
  • Must be able to understand new concepts quickly and apply them accurately throughout an evolving environment.
  • Strong communication, computer, and interpersonal skills are required to enable an effective interface with other professionals, to produce appropriate documentation, and to present results to a limited internal audience.
  • Must be able to work both independently and on a team.
  • Able to work extended hours as required.
  • Customer focused, must be able to work on a self-initiated basis and in a team environment, and able to work extended hours and travel as required.
  • Ability to obtain and maintain a DoD security clearance is required.

What General Atomics employees say

Pay

Benefits

Hours and flexibility

Workplace

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About General Atomics

Sourced by ZipRecruiter

General Atomics (GA), and its affiliated companies, is one of the world's leading resources for high-technology systems development ranging from the nuclear fuel cycle to remotely piloted aircraft, airborne sensors, and advanced electric, electronic, wireless and laser technologies.

Industry

Space research administration

Company size

10,000+ Employees

Headquarters location

San Diego, CA, US

Year founded

1955