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Entry Level Apple Machine Learning Engineer Jobs in Hercules, CA

Orchard

Machine Learning Engineer

San Francisco, CA · On-site

The Machine Learning Engineer will develop solutions for machine learning and computer vision software, working with large datasets to improve agricultural efficiency and sustainability.

Handshake

Machine Learning Engineer I

San Francisco, CA · On-site

$151K - $189K/yr

About the Role Handshake is hiring a Machine Learning Engineer I for the Growth Relevance team. AI is transforming how students navigate their careers, and we're committed to providing innovative ...

Elicit

Machine Learning Engineer

Oakland, CA · On-site +1

We invite you to help us build that future. (See how people use Elicit today on Twitter; explore our vision in the roadmap.) About the role As a Machine Learning Engineer at Elicit, you'll build ...

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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 Jul 31, 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, and why are they important?

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 Machine Learning Engineers at Apple, 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.
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

Orchard

San Francisco, CA • On-site

Full-time

Re-posted 9 days ago

Job description

Job Summary:
Orchard Robotics is a Series A startup focused on automating farming through AI technology. The Machine Learning Engineer will develop solutions for machine learning and computer vision software, working with large datasets to improve agricultural efficiency and sustainability.
Responsibilities:
• Build and maintain scalable ETL pipelines for processing large, diverse image datasets collected from our tractor-mounted camera systems in farms.
• Develop and deploy infrastructure for model training, evaluation, and inference, both in the cloud and on edge devices.
• Design and implement intelligent active sampling infrastructure to optimize data collection and improve model performance.
• Stay up-to-date with current literature in computer vision models and architectures, and apply relevant advancements to our systems.
• Collaborate with a multidisciplinary team to integrate ML solutions into production robotics systems.
• Work closely with agronomists and farmers to understand crop biology and translate domain knowledge into actionable ML features.
• Be a generalist, supporting different parts of our software stack as needed.
Qualifications:
Required:
• 2+ years of real-world, industry experience building production-grade data pipelines and ML infrastructure.
• Proficiency in Python and experience with ML frameworks (e.g., PyTorch).
• Strong experience with data engineering tools (e.g., Pandas, SQL, MLFlow, WandB).
• Familiarity with cloud platforms (AWS, GCP) and containerization (Docker, Kubernetes).
• Experience working with massive amounts of real-world training data.
• Familiarity with MLops software and data engineering to ensure consistent deployment of ML models.
• Ability to work independently, learn quickly, and operate in a dynamic environment.
• Enthusiasm for taking on multiple roles and responsibilities as our company grows.
Preferred:
• Experience deploying & optimizing ML models to run fast on embedded compute like NVIDIA Jetson.
• Experience prototyping, evaluating, or deploying new ML/CV models on the edge.
Company:
We're a team of engineers, researchers, and farmers on a mission to revolutionize one of Earth's most important industries – agriculture. Founded in 2022, the company is headquartered in Seattle, USA, with a team of 11-50 employees. The company is currently Early Stage.

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