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

... and machine learning space good in finance - Pittsburgh and Lake Mary are available office ... addition of Python development/engineering - Knowing Oracle and BigData is helpful as well ...

... learning. Everyone brings something unique, and together we push ideas forward to solve real ... Experience with Machine and Motion Controldesirable * Ability to understand and explain technical ...

Senior Vision Engineer

Weirton, WV · On-site

$102K - $140K/yr

Architect, design, and prototype industrial machine vision systems tailored to complex dimensional ... Bachelor's degree in Electrical Engineering, Mechanical Engineering, Computer Science, or a related ...

This opportunity is ideal for recent graduates or emerging professionals ready to transition from academic learning to impactful, real-world engineering. As a Staff I Engineer, you'll be part of a ...

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Showing results 1-20

Machine Learning Engineer information

See Toronto, OH salary details

$28.1K

$114.9K

$172.6K

How much do machine learning engineer jobs pay per year?

As of Jul 13, 2026, the average yearly pay for machine learning engineer in Toronto, OH is $114,866.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,500.00 and $138,300.00 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 cities near Toronto, OH are hiring for Machine Learning Engineer jobs? Cities near Toronto, OH with the most Machine Learning Engineer job openings:
Infographic showing various Machine Learning Engineer job openings in Toronto, OH as of July 2026, with employment types broken down into 94% Full Time, 3% Part Time, and 3% Contract. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $114,866 per year, or $55.2 per hour.
Machine Learning Operations Engineer - Pittsburgh, PA, Strongsville, OH, or Dallas, TX - Full Time

Machine Learning Operations Engineer - Pittsburgh, PA, Strongsville, OH, or Dallas, TX - Full Time

Lorven Technologies

Pittsburgh, PA • On-site

Full-time

Posted 3 days ago

New


Job description

Our client seeks an Machine Learning Operations Engineer for a Full Time project in Pittsburgh, PA, Strongsville, OH, or Dallas, TX. Below is the detailed requirement
Job Title: Machine Learning Operations Engineer
Work location : Pittsburgh, PA, Strongsville, OH, or Dallas, TX
Duration: Full Time
Summary:
Position Description
We are seeking an experienced MLOps Engineer with strong expertise in Python and big data technologies to join our team. This role focuses on operational excellence, including optimizing feature engineering pipelines and maintaining machine learning models in production environments. Desired candidate will work closely with platform and data science teams to ensure scalable, reliable, and high-performance ML workflows using existing frameworks.
Required qualifications to be successful in this role
  • Bachelor's degree preferably in Computer Science, Information technology, Computer Engineering, or related IT discipline or equivalent experience with 12+ Minimum Experience.
  • Amazon Web Services Cloud, Apache Hadoop YARN,Apache Kafka, AWS SageMaker,Big Data, Analytics & Operations,Hadoop Hive,Machine Learning,Pandas,Python
  • 6+ years of experience in software engineering, data engineering, or MLOps roles.
  • Strong programming expertise in Python, with hands-on experience in Pandas, PySpark, and PyArrow.
  • Deep understanding of the Hadoop ecosystem, distributed computing, and performance tuning.
  • Experience with CI/CD pipelines and best practices in ML environments.
  • Hands-on experience with monitoring tools for ML pipeline health and performance.
  • Strong collaboration skills with experience working in cross-functional teams (platform, data science, engineering).
  • Experience contributing to or building internal MLOps frameworks/platforms.
  • Familiarity with SLURM clusters or other distributed job schedulers.
  • Exposure to Kafka, Spark Streaming, or other real-time data processing technologies.
  • Understanding of ML lifecycle management, including versioning, deployment, and drift detection.

Lorven technologies logo

About Lorven technologies

Sourced by ZipRecruiter

Lorven Technologies, headquartered in Plainsboro, New Jersey, United States, is a reputable company in the technology industry, specializing in providing effective IT solutions and consulting services. The company's official website, lorventech.com, offers comprehensive insights into its offerings which include but are not limited to software development, IT consulting, project management, and business analysis. Since its inception, Lorven Technologies has been committed to ensuring efficiency and reliability in delivering IT services to its global clientele, establishing itself as a trusted name in the industry.

Industry

It services

Company size

51 - 200 Employees

Headquarters location

Plainsboro, NJ, US

Year founded

2001

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