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Entry Level Apple Machine Learning Engineer Jobs in Hercules, CA

Fluidstack

Machine Learning Engineer

San Francisco, CA · On-site

$130 - $180/hr

Partner with data engineering and product pods to put predictions in the tools people already use. What We're Looking For * The below is a starting point. We always make space for exceptional people ...

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All JobsApple Machine Learning Engineer JobsEntry Level Apple Machine Learning Engineer JobsEntry Level Apple Machine Learning Engineer Jobs in Hercules, CA

Entry Level Apple Machine Learning Engineer information

See Hercules, CA salary details

$33.1K

$76.6K

$130.3K

How much do entry level apple machine learning engineer jobs pay per year?

As of Aug 14, 2026, the average yearly pay for entry level apple machine learning engineer in Hercules, CA is $76,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $56,900.00 and $86,700.00 per year, depending on experience, location, and employer.

What does an entry level Apple machine learning engineer do?

An Entry Level Apple Machine Learning Engineer helps design, develop, and implement machine learning models and algorithms for Apple products and services. They work closely with senior engineers and data scientists to collect and analyze data, build prototypes, and improve the performance of machine learning systems. Responsibilities often include coding, model evaluation, and collaborating with cross-functional teams to integrate ML solutions into Apple’s ecosystem. This role is ideal for those with a strong foundation in programming, statistics, and a passion for innovative technology.

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

AspectEntry Level Apple Machine Learning EngineerEntry Level Data Scientist
Required CredentialsBachelor's in CS, ML, or related; knowledge of ML frameworksBachelor's in CS, Statistics, or related; strong analytical skills
Work EnvironmentTech company, R&D, product developmentData analysis, research, business insights
Employer & Industry UsageApple, consumer electronics, softwareVarious industries including tech, finance, healthcare
Common Search & ComparisonYesYes

Entry Level Apple Machine Learning Engineers focus on developing ML models for Apple products, requiring knowledge of ML frameworks and programming. Entry Level Data Scientists analyze data to derive insights, often with statistical expertise. While both roles involve data and programming, ML Engineers emphasize model deployment, whereas Data Scientists focus on data analysis and reporting.

What are the key skills and qualifications needed to thrive as an entry level Apple machine learning engineer?

To thrive as an Entry Level Apple Machine Learning Engineer, you generally need a solid background in computer science, mathematics, and statistics, often supported by a relevant degree and coursework in machine learning. Familiarity with programming languages such as Python or Swift, experience with machine learning frameworks like TensorFlow or PyTorch, and knowledge of Apple's development tools like Core ML are typically required. Strong problem-solving abilities, teamwork, and effective communication skills help you collaborate and contribute innovative solutions in a dynamic tech environment. These competencies are crucial for developing and optimizing machine learning models that power Apple's products and services.

What are some common challenges faced by entry level Apple machine learning engineers, and how can they overcome them?

Entry-level Machine Learning Engineers at Apple often encounter challenges such as adapting to the company's fast-paced innovation cycle, understanding large and complex codebases, and collaborating with cross-functional teams. To overcome these hurdles, it's important to proactively seek mentorship, participate in code reviews, and familiarize oneself with Apple's internal tools and documentation. Regular communication with peers and senior engineers can also help accelerate the learning curve and foster a collaborative environment that encourages innovation and knowledge sharing.

What job categories do people searching Entry Level Apple Machine Learning Engineer jobs in Hercules, CA look for?

The top searched job categories for Entry Level Apple Machine Learning Engineer jobs in Hercules, CA are:

Entry Level Apple Machine Learning Engineer jobs near you
Infographic showing various Entry Level Apple Machine Learning Engineer job openings in Hercules, CA as of June 2026, with employment types broken down into 4% As Needed, 43% Full Time, 47% Part Time, 2% Temporary, and 4% Contract. Highlights an 56% Physical, and 44% Remote job distribution, with an average salary of $76,584 per year, or $36.8 per hour.

Machine Learning Engineer - Robot Manipulation

Maven Robotics

San Francisco, CA

Full-time

Re-posted 12 days ago

Job description

Company Overview

Maven Robotics is building the world's leading general-purpose AI robots.

We are currently operating in stealth and are growing the world's best team in AI robotics. We are looking for self-starters that are the world's best in their field, who can innovate from a deep understanding of the fundamentals, and who share our values of unwavering truth seeking and integrity, humility, curiosity, and relentless determination.

Role Description

We are looking to recruit an exceptional Machine Learning Engineer - Robot Manipulation to design, implement, test, and deploy robot manipulation algorithms that enable assembly and material movement tasks.

In this role you will:

  • Design and implement machine learning algorithms, with a focus on reinforcement learning (RL) and imitation learning (IL), to enable robotic manipulators to perform complex tasks in dynamic environments.
  • Translate high-level objectives into machine learning problems and deploy robust, scalable models to real-world robotic systems.
  • Integrate your ML solutions into existing robotics workflows, ensuring that models are performant in both simulated and real-world settings.
  • Drive innovation by incorporating the latest research in machine learning into practical applications that push the boundaries of robotic manipulation.
  • Take ownership of critical ML projects, seeing them through from conception to successful deployment.
  • Collaborate across disciplines to ensure seamless integration of ML models and provide technical mentorship to junior engineers.
Qualifications

Must-have:

  • MS or PhD in machine learning, computer science, robotics, or a related field.
  • Strong practical experience in training and deploying machine learning models for real-world applications.
  • Deep understanding of reinforcement learning (RL) and imitation learning (IL) and their application to robotics.
  • Proficiency in programming languages and tools commonly used in machine learning (e.g., Python, PyTorch).
  • Experience with data collection, preprocessing, and management in the context of training ML models.
  • Self-starter attitude with strong ability to identify problems, prioritize them, then plan and execute working solutions.
  • Enthusiasm for working in a fast paced startup environment and eagerness to support the team on a variety of topics.

Nice-to-have:

  • Familiarity with robotic simulation environments (e.g., Gazebo, MuJoCo) and experience in sim-to-real transfer.
  • Experience in:
    • Designing and implementing reward functions for complex manipulation tasks.
    • Developing models that can handle noisy, incomplete, or sparse data.
    • Deployment of ML models to edge devices for real-time inference.
    • Accelerating ML training processes using GPU, TPU, or other HW accelerators.
    • Using reinforcement learning frameworks, e.g. Stable Baselines, RLlib, or similar.
  • General knowledge of robotics principles, including kinematics, dynamics, and control.
  • Publications or contributions to the machine learning community, particularly in areas related to robotics or reinforcement learning.

Apply