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Remote Machine Learning Jobs in Ohio (NOW HIRING)

Statheros

Experience : * 4+ years of professional experience in machine learning, with a focus on ... Remote work location. * Competitive salary. * Flexible work schedule. * Opportunities for ...

Huntington

Senior Data Scientist - AI

Columbus, OH · On-site +1

Conducts research on cutting-edge techniques and tools in machine learning/deep learning/artificial ... Remote roles will also have the opportunity to come together in our offices for moments that matter.

Huntington

Senior Data Scientist - AI

Columbus, OH · On-site +1

Conducts research on cutting-edge techniques and tools in machine learning/deep learning/artificial ... Remote roles will also have the opportunity to come together in our offices for moments that matter.

MMB Solutions LLC

Systems Engineer

Dayton, OH · On-site +1

This position will support development of a data architecture and machine learning experimentation ... This role is based in Dayton, Ohio with the possibility of remote work. Requirements U.S.

GRVTY

Software Engineer, Senior

Dayton, OH · On-site +1

$119K - $157K/yr

Develop and integrate machine learning workflows - including training data preparation, model ... Background in signal processing, image processing, or remote sensing data workflows. * Experience ...

GRVTY

Software Engineer, Senior

Dayton, OH · On-site +1

$119K - $157K/yr

Develop and integrate machine learning workflows - including training data preparation, model ... Background in signal processing, image processing, or remote sensing data workflows. * Experience ...

GRVTY

Software Engineer, Senior

Dayton, OH · On-site +1

$119K - $157K/yr

Develop and integrate machine learning workflows -- including training data preparation, model ... Background in signal processing, image processing, or remote sensing data workflows. * Experience ...

Rackner

AI/ML Engineer (Active TS/SCI )

Dayton, OH · On-site +1

Design, develop, and implement machine learning and deep learning models * Build and optimize model ... Weekly pay with full remote flexibility * Professional growth investment, including paid ...

Rackner

AI/ML Engineer (Active TS/SCI )

Dayton, OH · On-site +1

Design, develop, and implement machine learning and deep learning models * Build and optimize model ... Weekly pay with full remote flexibility * Professional growth investment, including paid ...

ERP Suites

AI & Mobile Product Manager

Loveland, OH · On-site +1

Although the position will be remote, there might be some occasional travel to ERP Suites ... Core Competencies: • Product strategy and roadmap development • AI, machine learning ...

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All JobsMachine Learning JobsRemote Machine Learning JobsRemote Machine Learning Jobs in Ohio

Remote Machine Learning information

See Ohio salary details

$24.2K

$40.5K

$83.7K

How much do remote machine learning jobs pay per year?

As of Jul 8, 2026, the average yearly pay for remote machine learning in Ohio is $40,484.00, according to ZipRecruiter salary data. Most workers in this role earn between $30,900.00 and $43,700.00 per year, depending on experience, location, and employer.

What engineer makes $500,000 a year?

Senior machine learning engineers with extensive experience, advanced skills in deep learning and data modeling, and often working at large tech companies or in specialized industries can earn salaries approaching or exceeding $500,000 annually. Compensation may include base salary, bonuses, and stock options, especially in high-demand markets.

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

To thrive as a Remote Machine Learning Engineer, you need a strong background in mathematics, statistics, programming (often Python), and experience with machine learning frameworks, typically supported by a relevant degree. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (like AWS or GCP), and version control systems is crucial. Strong problem-solving abilities, self-management, and effective virtual communication distinguish top performers in remote settings. These competencies ensure the engineer can build effective models, collaborate across distributed teams, and deliver impactful solutions independently.

How to make 2000 a week working from home?

Remote machine learning professionals can earn $2,000 or more weekly by taking on high-paying freelance projects, consulting roles, or working for companies that offer remote positions with competitive salaries. Building specialized skills in programming, data analysis, and tools like Python, TensorFlow, or cloud platforms can increase earning potential. Consistent work, a strong portfolio, and networking are key to reaching this income level from home.

What Are Remote Machine Learning Jobs?

Machine learning is a method of analyzing data via automating analytical model building. The premise is that systems can learn from data. Machine learning positions include machine learning engineer, computer vision engineer, and senior deep learning engineer. In a remote machine learning job, you work from home in a branch of artificial intelligence performing duties related to computational processing and data. Your goal is to design models that solve business problems, such as helping organizations avoid unknown risks or find profitable opportunities. Your responsibilities include maintaining data pipelines, performing model research and implementation, building machine learning systems, and onboarding new utilities.

What is a remote machine learning job?

A remote machine learning job involves working with algorithms, data, and models to develop predictive systems or automate tasks, all while working from a location outside of a traditional office setting. Professionals in this role use techniques from statistics and computer science to analyze data, train machine learning models, and deploy solutions for real-world applications. Remote machine learning jobs can span various industries, including technology, healthcare, finance, and e-commerce. These roles typically require strong programming skills, knowledge of machine learning frameworks, and the ability to communicate findings effectively with team members or stakeholders. Working remotely offers flexibility, but also requires discipline and self-motivation to succeed.

What are some effective strategies for collaborating with team members while working remotely as a Machine Learning Engineer?

Collaboration in a remote Machine Learning role often relies on clear communication through digital tools such as Slack, Zoom, and project management platforms like Jira or Asana. Regular check-ins and stand-up meetings help keep everyone aligned on project goals and timelines. Sharing code and models via version control systems (like Git) and using collaborative notebooks (such as JupyterHub or Google Colab) are also common practices. Building strong documentation habits and proactively seeking feedback can help ensure smooth teamwork and project success, even across different time zones.

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

AspectRemote Machine LearningData Scientist
Required CredentialsBachelor's/Master's in CS, ML certificationsBachelor's/Master's in CS, Statistics, or related field
Work EnvironmentRemote, collaborative teams, tech companiesRemote or on-site, diverse industries, analytics focus
Industry UsageTech, AI startups, researchFinance, healthcare, e-commerce, tech
Search & Comparison IntentOften compared for technical roles in AI/MLBroader data analysis roles, but overlapping skills

Remote Machine Learning specialists focus on developing algorithms and models primarily in tech environments, often requiring advanced programming and ML knowledge. Data Scientists analyze data to extract insights, sometimes utilizing ML techniques. While both roles share skills and credentials, Remote Machine Learning emphasizes model development, whereas Data Scientists focus on data analysis and interpretation.

Are there remote machine learning jobs?

Yes, remote machine learning jobs are widely available across various industries, often requiring skills in programming, data analysis, and familiarity with tools like Python, TensorFlow, or PyTorch. Many companies offer flexible schedules and remote work options for qualified candidates, especially in tech and research sectors.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and deploy AI models, and their role involves understanding algorithms, data preprocessing, and model optimization. While AI automation tools can handle certain tasks, MLEs are essential for creating, fine-tuning, and maintaining complex AI systems, making complete replacement unlikely in the near term.
More about Remote Machine Learning jobs
What are the most commonly searched types of Machine Learning jobs in Ohio? The most popular types of Machine Learning jobs in Ohio are:
What are popular job titles related to Remote Machine Learning jobs in Ohio? For Remote Machine Learning jobs in Ohio, the most frequently searched job titles are:
What job categories do people searching Remote Machine Learning jobs in Ohio look for? The top searched job categories for Remote Machine Learning jobs in Ohio are:
What cities in Ohio are hiring for Remote Machine Learning jobs? Cities in Ohio with the most Remote Machine Learning job openings:
Remote Machine Learning jobs near you
WFP Machine Learning Scientist

WFP Machine Learning Scientist

J.P. Morgan

Columbus, OH • On-site, Remote

Full-time

Medical, Retirement

Posted 8 days ago

Job description

hackajob is collaborating with J.P. Morgan to connect them with exceptional professionals for this role.

JOB DESCRIPTION

The Workforce Planning (WFP) organization is a part of Consumer and Community (CCB) Operations division. The WFP Data Science organization is tasked with delivering quantitatively driven solutions to support the core WFP functions (demand forecasting, capacity planning, resource scheduling, and business analysis & support). The WFP organization supports Chase’s call centers, back office, and ~5,200 retail branches.

As a Data Scientist Lead - WFP Machine Learning Scientist, within JPMorganChase, you will engage in projects by the Artificial Intelligence(AI)/Machine Learning(ML) team that can be complex, data intensive, and of a high level of difficulty, each having significant impact on the business.  You will typically encounter these problems which will be of an unstructured nature, whereby the employee will be expected to quickly assess and comprehend the situation then develop a practical problem solving strategy.  You will be expected to analyze the topic in question, develop solution proposals and review their results and next steps with management for prioritization, timing, and delivery. The AI/ML team is tasked with building next-gen data science solutions that move us closer to real-time inference and decision making.

Job Responsibilities

  • Design and development of Machine Learning, Artificial Intelligence and Statistical models.
  • Participate in the full model development lifecycle, from framing the problem to prepare documentation and passing independent model review (MRGR).
  • Lead AI/ML projects along with mentor and coach junior team members.
  • Collaborate with stakeholders to understand the business requirements and clearly define the objectives of any solution.
  • Identify and select the correct method to solve the problem while staying up to data on the latest AI/ML research
  • Ensure the robustness of any data science solution.
  • Develop and communicate recommendations and data science solutions in easy-to-understand-way leveraging data to tell a story.
  • Lead and persuade others while positively influencing the outcome of team efforts and help frame a business problem into a technical problem resulting in a feasible solution.

Required Qualifications, Capabilities, and Skills

  • Master’s Degree with 5+ years or Doctorate (PhD) with 3+ years of experience operating as an data science professional (e.g. data scientist, statistician, or related professions) in a quantitative field: Statistics, Analytics, Data Science, Engineering, Operations Research, Economics, Mathematics, Machine Learning, Artificial Intelligence, and related disciplines.
  • 2+ years of experience leading AI/ML projects with multiple team members
  • Hands-on experience developing statistical models, machine learning models, and/or artificial intelligence models.
  • Deep understanding of math and theory behind AI/ML algorithms.
  • Proficient in data science programming languages like Python, R or Scala.
  • Experience with big-data technologies such as Hadoop, Spark, SparkML, etc. & familiarity with basic data table operations (SQL, Hive, etc.).
  • Demonstrated relationship building skills, with a superior ability to make things happen through the use of positive influence. 

Preferred Qualifications, Capabilities, and Skills

  • Advanced expertise with Time Series and Operations Research techniques. 
  • Natural Language Processing(NLP)/Natural Language Generation(NLG), Neural Nets, or other ML/AI skills.
  • Prior experience with public cloud technologies such as Amazon Web Services(AWS), Azure or Google Cloud Platform(GCP).
  • Previous experience leading highly complex cross-functional technical projects with multiple stakeholders

This position is full time in office Monday - Friday.  This position is not hybrid nor remote.

ABOUT US

Chase is a leading financial services firm, helping nearly half of America’s households and small businesses achieve their financial goals through a broad range of financial products. Our mission is to create engaged, lifelong relationships and put our customers at the heart of everything we do. We also help small businesses, nonprofits and cities grow, delivering solutions to solve all their financial needs. 

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions.  We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants’ and employees’ religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

Equal Opportunity Employer/Disability/Veterans

ABOUT THE TEAM
Our Consumer & Community Banking division serves our Chase customers through a range of financial services, including personal banking, credit cards, mortgages, auto financing, investment advice, small business loans and payment processing. We’re proud to lead the U.S. in credit card sales and deposit growth and have the most-used digital solutions – all while ranking first in customer satisfaction.
The CCB Data & Analytics team responsibly leverages data across Chase to build competitive advantages for the businesses while providing value and protection for customers. The team encompasses a variety of disciplines from data governance and strategy to reporting, data science and machine learning. We have a strong partnership with Technology, which provides cutting edge data and analytics infrastructure. The team powers Chase with insights to create the best customer and business outcomes.

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