ZipRecruiter

Log In

2

Entry Level Machine Learning Engineer Jobs in Cincinnati, OH

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 ...

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

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 ...

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 ...

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

$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

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 ...

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 ...

next page

Showing results 1-20

All JobsMachine Learning Engineer JobsEntry Level Machine Learning Engineer JobsEntry Level Machine Learning Engineer Jobs in Cincinnati, OH

Entry Level Machine Learning Engineer information

See Cincinnati, OH salary details

$28.8K

$66.6K

$113.3K

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

As of Aug 24, 2026, the average yearly pay for entry level machine learning engineer in Cincinnati, OH is $66,604.00, according to ZipRecruiter salary data. Most workers in this role earn between $49,500.00 and $75,400.00 per year, depending on experience, location, and employer.

What is an entry level machine learning engineer?

An Entry Level Machine Learning Engineer is responsible for developing, testing, and deploying machine learning models under the guidance of senior engineers. They work with datasets, implement algorithms, and optimize model performance. Their role often involves data preprocessing, feature engineering, and collaborating with data scientists and software engineers. Strong programming skills in Python, knowledge of ML frameworks like TensorFlow or PyTorch, and an understanding of statistics and algorithms are essential. This position serves as a foundation for building expertise in artificial intelligence and data-driven decision-making.

What are some typical projects or tasks an entry level machine learning engineer might work on?

As an Entry Level Machine Learning Engineer, you’ll often work on tasks such as data preprocessing, feature engineering, and assisting in training and evaluating models under the guidance of senior engineers or data scientists. You may help develop prototypes, automate data collection pipelines, and collaborate with software engineers to integrate machine learning solutions into products. Working in this role typically involves frequent collaboration in a team environment, participating in code reviews, and learning best practices for scalable model deployment. These foundational experiences are designed to build your technical expertise and set the stage for future growth within the field.

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

To thrive as an Entry Level Machine Learning Engineer, you need a solid understanding of machine learning algorithms, programming languages like Python, and a degree in computer science, engineering, or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is highly valuable, and completing online courses or certifications can further demonstrate your skills. Strong analytical thinking, attention to detail, and effective communication are important soft skills in this role. These abilities are essential because they enable you to build accurate models, work collaboratively with teams, and communicate insights to stakeholders.

What are the most commonly searched types of Machine Learning Engineer jobs in Cincinnati, OH?

The most popular types of Machine Learning Engineer jobs in Cincinnati, OH are:

What are popular job titles related to Entry Level Machine Learning Engineer jobs in Cincinnati, OH?

For Entry Level Machine Learning Engineer jobs in Cincinnati, OH, the most frequently searched job titles are:

What job categories do people searching Entry Level Machine Learning Engineer jobs in Cincinnati, OH look for?

The top searched job categories for Entry Level Machine Learning Engineer jobs in Cincinnati, OH are:

What cities near Cincinnati, OH are hiring for Entry Level Machine Learning Engineer jobs?

Cities near Cincinnati, OH with the most Entry Level Machine Learning Engineer job openings:

Entry Level Machine Learning Engineer jobs near you
Infographic showing various Entry Level Machine Learning Engineer job openings in Cincinnati, OH as of August 2026, with employment types broken down into 77% Full Time, and 23% Contract. Highlights an 92% In-person, and 8% Remote job distribution, with an average salary of $66,604 per year, or $32 per hour.

Senior Machine Learning Engineer

Incedo Inc

Cincinnati, OH • On-site

$100K - $137K/yr

Other

Posted 4 days ago

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.

Apply