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

SysMind Tech

Data Engineer - Databricks

Pittsburgh, PA · On-site

$108K - $130K/yr

Role: Data Engineer Location: Warrendale, PA / Pittsburgh, PA (Onsite) Job Type: Contract Role Overview We are seeking an experienced Data Engineer with strong expertise in Databricks, Python, and ...

Form Energy

Staff NPI Project Engineer

Weirton, WV · On-site

This role sits within Operations Engineering and works in close partnership with our Technical Program Manager to ensure that every change - from next-generation pack-level design updates to ...

Eaton

Senior Connected Integration Engineer

PA · On-site +1

$97K - $143K/yr

The position supports end users and field engineers with product installation, device configuration, and data acquisition requirements, ensuring accurate and timely resolution. Responsibilities ...

Form Energy

Senior Equipment Engineer, Operations

Weirton, WV · On-site

$102K - $140K/yr

Role Description We're looking for a Senior Equipment Engineer to join our Operations Engineering team. In this role, you will use your deep familiarity with a variety of manufacturing equipment to ...

Eaton

Lead Design Engineer

PA · On-site

$97K - $143K/yr

Eaton's ES AMER ARS division is currently seeking a Lead Design Engineer to join our team in our Cherrington Office - Moon Township, PA. The expected annual salary range for this role is $97000 ...

ABB

Sales Specialist - Automation

PA

... learning. Everyone brings something unique, and together we push ideas forward to solve real ... Bachelors degree in Engineering (Mechatronics, Mechanical, Electrical or similar) or equivalent ...

Adobe

Senior AEM Forward Deployed Engineer

Toronto, OH · On-site

$93K - $128K/yr

As part of the AEM Co-Innovation Engineering (ACE) team, you'll play a critical role in evolving the Adobe Experience Manager product. What You'll Do * Collaborate & Innovate: Demonstrate your strong ...

Mondi AG

Safety, Health and Environment Manager

Clinton, PA · On-site

$82K - $111K/yr

LOTO, Working at Heights, Confined Space Entry, Machine Guarding, and Chemical Safety * Coach ... Bachelor's degree in Environmental Engineering, Occupational Safety, Industrial Hygiene, or related ...

Mondi AG

Safety, Health and Environment Manager

Clinton, PA · On-site

$82K - $111K/yr

LOTO, Working at Heights, Confined Space Entry, Machine Guarding, and Chemical Safety * Coach ... Bachelor's degree in Environmental Engineering, Occupational Safety, Industrial Hygiene, or related ...

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Showing results 1-20

All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Toronto, OH

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.

More about Machine Learning Engineer jobs
What cities near Toronto, OH are hiring for Machine Learning Engineer jobs? Cities near Toronto, OH with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
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.

Data Engineer - Databricks

SysMind Tech

Pittsburgh, PA • On-site

$108K - $130K/yr

Contractor

Re-posted 27 days ago

Job description

Role: Data Engineer
Location: Warrendale, PA / Pittsburgh, PA (Onsite)
Job Type: Contract
Role Overview
We are seeking an experienced Data Engineer with strong expertise in Databricks, Python, and Spark to design and build scalable data pipelines. The ideal candidate will have hands-on experience with ETL/ELT development and large-scale data processing using Spark and PySpark.
Key Responsibilities
  • Design, develop, and maintain ETL/ELT data pipelines for large-scale data processing.
  • Build scalable data solutions using Databricks and Apache Spark (PySpark / Spark SQL).
  • Develop and optimize Python-based data processing frameworks.
  • Work closely with data analysts and data scientists to deliver high-quality datasets.
  • Optimize performance and scalability of data pipelines.
  • Implement data quality checks and monitoring solutions.
  • Collaborate with cross-functional teams to support analytics and reporting initiatives.

Required Skills
  • Advanced Databricks (hands-on experience)
  • Strong Python programming
  • Spark / PySpark / Spark SQL
  • ETL / ELT pipeline development
  • Data pipeline optimization and performance tuning
  • Strong SQL skills

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