1

Machine Learning Engineer Jobs in Cleveland, OH (NOW HIRING)

... prompt engineering workflows and fine-tune models using domain-specific data • Evaluate and benchmark machine learning and LLM model performance • Work with large-scale structured and ...

Data Engineer

Highland Heights, OH · On-site

$111K - $133K/yr

Develop machine learning and regression analysis skills in spark-python-pandas, openai and Azure ML. * Employ Azure Devops and Git in line with the Software Development Life Cycle best practices.

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

NGA AI Engineer Manager

Cleveland, OH · On-site

$73K - $244K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

Python Developer

Strongsville, OH · On-site

$46.25 - $64/hr

Python Programming: Proficiency in Python language and its ecosystem. * Frameworks: Knowledge of ... Data Analysis/Machine Learning: Utilizing Python libraries like Pandas, NumPy, and Scikit-learn for ...

Engineer

Cleveland, OH · On-site

$100K - $120K/yr

Strong programming background in Python, deep understanding of machine learning algorithm. * Evaluate and select appropriate AI frameworks, tools and cloud services. * Lead the architecture, design ...

Those in data science and machine learning engineering at PwC will focus on leveraging advanced analytics and machine learning techniques to extract insights from large datasets and drive data-driven ...

AI Engineer

Westlake, OH · On-site

$106K - $127K/yr

Applied AI and Machine Learning • Build and support predictive models and AI-assisted workflows using governed data from the lakehouse. • Develop feature engineering approaches for use cases such ...

next page

Showing results 1-20

Machine Learning Engineer information

See Cleveland, OH salary details

$30.5K

$124.7K

$187.4K

How much do machine learning engineer jobs pay per year?

As of Jul 15, 2026, the average yearly pay for machine learning engineer in Cleveland, OH is $124,694.00, according to ZipRecruiter salary data. Most workers in this role earn between $98,300.00 and $150,100.00 per year, depending on experience, location, and employer.

What engineers make $500,000?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data science, and often working in high-demand industries or companies can earn $500,000 or more annually. Compensation typically includes base salary, bonuses, and stock options, especially in tech giants or startups with significant funding.

What do machine learning engineers do?

Machine learning engineers develop algorithms and models that enable computers to learn from data and make predictions or decisions. They often work with large datasets, use programming languages like Python or Java, and utilize tools such as TensorFlow or PyTorch to build, test, and deploy machine learning systems in production environments.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

Which 5 jobs will survive AI?

Machine Learning Engineers are likely to continue to be in demand as AI advances, as they develop and refine algorithms, models, and systems. Roles that require complex problem-solving, creativity, and domain expertise—such as healthcare professionals, data scientists, software developers, cybersecurity specialists, and AI ethics officers—are also expected to persist due to their reliance on human judgment and specialized knowledge. These jobs often involve skills that are difficult for AI to fully replicate or replace.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What engineers make $300,000 a year?

Senior machine learning engineers and data scientists with extensive experience, advanced skills in deep learning, and proficiency with tools like TensorFlow or PyTorch can earn $300,000 or more annually, especially in high-cost-of-living areas or top tech companies. Compensation often includes base salary, bonuses, and stock options, reflecting their expertise and impact on business outcomes.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Cleveland, OH? The most popular types of Machine Learning Engineer jobs in Cleveland, OH are:
What are popular job titles related to Machine Learning Engineer jobs in Cleveland, OH? For Machine Learning Engineer jobs in Cleveland, OH, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer jobs in Cleveland, OH look for? The top searched job categories for Machine Learning Engineer jobs in Cleveland, OH are:
What cities near Cleveland, OH are hiring for Machine Learning Engineer jobs? Cities near Cleveland, OH with the most Machine Learning Engineer job openings:
Infographic showing various Machine Learning Engineer job openings in Cleveland, OH as of July 2026, with employment types broken down into 89% Full Time, and 11% Contract. Highlights an 78% In-person, 11% Hybrid, and 11% Remote job distribution, with an average salary of $124,694 per year, or $59.9 per hour.
Senior Data Scientist

Senior Data Scientist

Flexjet

Cleveland, OH • On-site

Full-time

Posted 9 days ago


Flexjet rating

8.2

Company rating: 8.2 out of 10

Based on 24 frontline employees who took The Breakroom Quiz

9th of 54 rated aviation services


Job description

Job Summary:
Flexjet is seeking a Senior-Level Enterprise AI Data Scientist to design, develop, and deploy enterprise-scale AI and Generative AI solutions that improve productivity, automate workflows, and enhance decision-making across the organization. This role focuses on building LLM-powered enterprise applications and requires collaboration with various teams to create secure and scalable AI solutions.
Responsibilities:
• Design and implement enterprise-scale machine learning models, including predictive and classification systems
• Develop intelligent automation solutions to streamline business workflows
• Build and deploy LLM-powered applications, such as enterprise knowledge assistants and chatbots
• Design and implement Retrieval-Augmented Generation (RAG) pipelines
• Develop solutions for semantic search, document intelligence, and enterprise search capabilities
• Optimize prompt engineering workflows and fine-tune models using domain-specific data
• Evaluate and benchmark machine learning and LLM model performance
• Work with large-scale structured and unstructured data sources across enterprise systems
• Design and build scalable data pipelines to support AI and machine learning workflows
• Integrate AI solutions with internal systems, APIs, and enterprise platforms
• Partner with data engineering teams to design and optimize data architectures
• Deploy AI/ML models into production environments
• Implement model monitoring, performance tracking, and alerting
• Maintain model versioning, reproducibility, and lifecycle management
• Support and contribute to CI/CD pipelines for AI and ML deployments
• Ensure scalability, reliability, and performance of systems in production environments
• Implement responsible AI practices, including fairness, transparency, and risk mitigation
• Ensure compliance with enterprise data governance, privacy, and security standards
• Support model explainability and documentation requirements
• Maintain thorough documentation of models, systems, and workflows
• Translate business needs into actionable technical solutions
• Work closely with product, engineering, and analytics teams to deliver AI-driven solutions
• Communicate technical concepts and solutions clearly to non-technical stakeholders
• Contribute to system architecture decisions and design discussions
• Document workflows, design decisions, and results
Qualifications:
Required:
• Bachelor's or master's degree in computer science, Information Technology, Data Science, or a related field, or an equivalent combination of education, training, and relevant professional experience.
• 5+ years of experience in Data Science, Machine Learning, and AI software engineering, machine learning engineering, platform engineering, MLOps, or DevOps.
• Experience building and deploying production ML systems
• Hands-on expertise in data preprocessing, feature engineering, and model evaluation
• Experience working with APIs, large datasets, and enterprise systems
• Strong proficiency in Python and SQL
• Experience developing and deploying models (regression, classification, clustering, ensembles, neural networks)
• Strong understanding of data preprocessing, feature engineering, and model evaluation
• Prompt engineering and optimization
• Retrieval-Augmented Generation (RAG)
• Embeddings and vector search
• Model evaluation and fine-tuning
• Experience working with large, complex datasets
• Data pipelines, ETL processes, and enterprise data warehouses
• API integrations and distributed/enterprise-scale systems
• Building and maintaining production-ready ML systems
• Familiarity with Docker, Kubernetes, and REST APIs
• CI/CD pipelines and version control (Git)
• Experience with AWS, Azure, or Google Cloud
Preferred:
• Experience developing LLM-powered applications in enterprise environments
• Hands-on experience with RAG pipelines, embeddings, and vector databases
• Strong understanding of prompt engineering and LLM evaluation techniques
• Familiarity with frameworks such as LangChain, LlamaIndex, and Hugging Face
• Knowledge of MLOps practices, including CI/CD, model monitoring, and lifecycle management
• Experience with Docker, Kubernetes, and containerized deployments
• Understanding of data governance, responsible AI, and model explainability
Company:
Flexjet is a private jet company that provides fractional jet ownership, leasing, and jet card services. Founded in 1995, the company is headquartered in Cleveland, USA, with a team of 501-1000 employees. The company is currently Late Stage.

What Flexjet employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom