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Entry Level Apple Machine Learning Engineer Jobs in Greendale, IN

Incedo Inc

Senior Machine Learning Engineer

Cincinnati, OH · On-site

$100K - $137K/yr

We are seeking an experienced Machine Learning Engineer with a strong bias for action, an ownership mindset, and a passion for solving complex business problems through automation and AI. The ideal ...

New

Varsity Tutors

Machine Learning Tutor

Cincinnati, OH · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Hudson Manpower

DATA ENGINEER IV

Cincinnati, OH · On-site

$68 - $70/hr

Machine Learning Data Enablement squad in the Data Insights Tribe Required: In office 4 days a week minimum (Monday-Thursday) We're hiring a Data Engineer to join our newly launched Machine Learning ...

Medpace, Inc.

AI Engineer

Cincinnati, OH · On-site +1

$109K - $132K/yr

Research, develop, and implement machine learning algorithms and models for tasks such as ... Technical proficiency in programming languages and frameworks commonly used in NLP and AI (e.g ...

Medpace, Inc.

AI Engineer

Cincinnati, OH · On-site

$109K - $132K/yr

Research, develop, and implement machine learning algorithms and models for tasks such as ... Technical proficiency in programming languages and frameworks commonly used in NLP and AI (e.g ...

Medpace

AI Engineer

Cincinnati, OH · On-site

$120 - $180/hr

Research, develop, and implement machine learning algorithms and models for tasks such as ... Technical proficiency in programming languages and frameworks commonly used in NLP and AI (e.g ...

Tata Consultancy Service Limited

Engineer

Cincinnati, OH · On-site

$100K - $110K/yr

GEN AI Developer • GenAI Application Engineer with strong core development skills in Java, Spring Boot, APIs, and Microservices • At least one must have concrete machine learning experience. • ...

Proctor & Gamble

Data Scientist

Cincinnati, OH · On-site

$85K - $122K/yr

Proficient in programming languages such as Python and familiar with data science/machine learning ... Job Schedule Full time Job Number R000135859 Job Segmentation Entry Level Starting Pay / Salary ...

Procter & Gamble Company

AI Engineer

Cincinnati, OH · On-site

Operationalizes Machine Learning models as integral element of IT solutions & business process ... Job Schedule Full time Job Number R000153947 Job Segmentation Entry Level Starting Pay / Salary ...

Proctor & Gamble

AI Engineer

Cincinnati, OH · On-site

Operationalizes Machine Learning models as integral element of IT solutions & business process ... Job Schedule Full time Job Number R000153947 Job Segmentation Entry Level Starting Pay / Salary ...

Great American Insurance Group

Data Engineer

Cincinnati, OH · On-site +1

$109K - $131K/yr

Support data engineering needs for predictive analytics and machine learning initiatives, including feature engineering, data preparation, and model enablement * Assist in modernizing data platforms ...

New

Great American Insurance Group

Data Engineer

Cincinnati, OH · On-site

$109K - $131K/yr

Support data engineering needs for predictive analytics and machine learning initiatives, including feature engineering, data preparation, and model enablement * Assist in modernizing data platforms ...

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All JobsApple Machine Learning Engineer JobsEntry Level Apple Machine Learning Engineer JobsEntry Level Apple Machine Learning Engineer Jobs in Greendale, IN

Entry Level Apple Machine Learning Engineer information

See Greendale, IN salary details

$27.2K

$63K

$107.2K

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

As of Aug 22, 2026, the average yearly pay for entry level apple machine learning engineer in Greendale, IN is $62,997.00, according to ZipRecruiter salary data. Most workers in this role earn between $46,800.00 and $71,300.00 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 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 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 cities near Greendale, IN are hiring for Entry Level Apple Machine Learning Engineer jobs?

Cities near Greendale, IN with the most Entry Level Apple Machine Learning Engineer job openings:

Entry Level Apple Machine Learning Engineer jobs near you
Infographic showing various Entry Level Apple Machine Learning Engineer job openings in Greendale, IN as of June 2026, with employment types broken down into 4% As Needed, 39% Full Time, 53% Part Time, 2% Temporary, and 2% Contract. Highlights an 64% Physical, and 36% Remote job distribution, with an average salary of $62,997 per year, or $30.3 per hour.

Senior Machine Learning Engineer

Incedo Inc

Cincinnati, OH • On-site

$100K - $137K/yr

Other

Posted 3 days ago

New

Job description

We are seeking an experienced Machine Learning Engineer with a strong bias for action, an ownership mindset, and a passion for solving complex business problems through automation and AI. The ideal candidate demonstrates technical excellence, leads by example, and has proven experience delivering enterprise-grade machine learning and Generative AI solutions in regulated environments.

Key Responsibilities

  • Design, develop, deploy, and maintain scalable machine learning and Generative AI solutions with a focus on reliability, performance, security, and business value.
  • Champion an automation-first approach to software and AI engineering, identifying opportunities to improve operational efficiency and reduce manual processes.
  • Build and operationalize machine learning models and AI-enabled applications throughout the entire model lifecycle, from experimentation to production deployment and monitoring.
  • Develop and deploy Generative AI applications in production environments, preferably within financial services or other highly regulated industries.
  • Apply and advocate Responsible AI principles, ensuring solutions meet requirements for fairness, explainability, transparency, privacy, security, and compliance.
  • Perform model risk evaluations, complete required governance documentation and questionnaires, and partner with stakeholders to address and remediate identified risks.
  • Establish and maintain frameworks for MLOps, model lifecycle management, monitoring, validation, version control, auditability, and AI governance.
  • Collaborate with Risk, Compliance, Information Security, and business partners to ensure machine learning solutions meet enterprise and regulatory standards.
  • Implement CI/CD pipelines, automated testing, model monitoring, observability, and production support processes for machine learning applications.
  • Evaluate emerging machine learning and AI technologies and recommend appropriate adoption strategies.
  • Mentor team members on best practices in machine learning engineering, MLOps, Responsible AI, and production AI systems.

Required Qualifications

  • Extensive experience designing, developing, and deploying machine learning solutions in production environments.
  • Hands-on experience developing and deploying Generative AI applications using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), vector databases, and modern AI development frameworks.
  • Strong understanding of machine learning model development, feature engineering, model evaluation, performance optimization, and model monitoring.
  • Experience conducting model risk assessments and supporting governance, compliance, and validation requirements within regulated environments.
  • Practical experience implementing MLOps practices including model deployment, versioning, monitoring, automated retraining, and CI/CD pipelines.
  • Strong understanding of Responsible AI, model explainability, governance, and risk management concepts.
  • Proficiency in Python and modern machine learning ecosystems, including frameworks such as TensorFlow, PyTorch, Scikit-learn, LangChain, Semantic Kernel, or equivalent technologies.
  • Strong communication, problem-solving, and stakeholder management skills.

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