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Remote Deep Learning Engineer Jobs in Ohio (NOW HIRING)

Develop and train reinforcement learning models for real-world applications, focusing on efficiency ... Remote work location. * Competitive salary. * Flexible work schedule. * Opportunities for ...

Utilize NLP algorithms and other deep learning techniques to process and analyze unstructured ... Lead development from prototype through production in partnership with engineering/architecture.

This role is based in Dayton, Ohio with the possibility of remote work. Requirements U.S ... Data Enrichment and Machine Learning Integration Develop and support automated data enrichment ...

Senior AI Engineer

Cleveland, OH · On-site +1

$101K - $139K/yr

Deep experience building production applications with LLM frameworks such as LangChain, LangGraph ... Conduct code reviews, provide technical guidance, and foster a culture of continuous learning and ...

Backend Engineer

Dublin, OH · Remote

$120K - $155K/yr

Deep knowledge of AWS services including ECS, Lambda, API Gateway, S3, CloudWatch, IAM, RDS Aurora ... AssetWatch is a remote-first company that puts people at the center of everything we do. We want ...

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Remote Deep Learning Engineer information

See Ohio salary details

$10.5K

$79.8K

$133.1K

How much do remote deep learning engineer jobs pay per year?

As of Jul 9, 2026, the average yearly pay for remote deep learning engineer in Ohio is $79,750.00, according to ZipRecruiter salary data. Most workers in this role earn between $68,400.00 and $132,100.00 per year, depending on experience, location, and employer.

How do Remote Deep Learning Engineers typically collaborate with cross-functional teams despite working remotely?

Remote Deep Learning Engineers frequently collaborate with data scientists, product managers, and software engineers using digital tools such as Slack, Zoom, and collaborative code platforms like GitHub. Regular virtual meetings and sprint planning sessions help ensure alignment on project goals and milestones. Clear documentation and asynchronous communication are crucial for effective teamwork, especially when team members are in different time zones. This collaborative structure enables remote engineers to contribute meaningfully to model development, deployment, and integration while maintaining flexibility.

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

To thrive as a Remote Deep Learning Engineer, you need a strong background in machine learning, deep learning frameworks, and programming languages like Python, usually supported by a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, cloud platforms (e.g., AWS, GCP), and version control systems is typically required, with certifications in AI or cloud technologies being advantageous. Excellent problem-solving, communication, and self-management skills make candidates stand out in remote environments. These skills and qualities are essential for developing effective AI solutions, collaborating across distributed teams, and driving innovation in the fast-evolving field of deep learning.

What is the difference between Remote Deep Learning Engineer vs Remote Machine Learning Engineer?

AspectRemote Deep Learning EngineerRemote Machine Learning Engineer
Required CredentialsBachelor's/Master's in CS, AI, or related; experience with deep learning frameworksBachelor's/Master's in CS, Data Science, or related; experience with ML algorithms
Work EnvironmentResearch and development, model training, neural network designData analysis, model deployment, algorithm development
Employer & Industry UsageTech companies, AI startups, research institutionsTech firms, finance, healthcare, e-commerce

Remote Deep Learning Engineers focus on designing and training neural networks for complex AI tasks, while Remote Machine Learning Engineers work on broader ML models and algorithms. Both roles require strong programming skills and knowledge of machine learning frameworks, but Deep Learning Engineers specialize in neural networks and large-scale data processing.

What is a Remote Deep Learning Engineer?

A Remote Deep Learning Engineer is a professional who works primarily online to design, develop, and implement deep learning models and algorithms. These engineers use neural networks and large datasets to solve complex problems in fields like computer vision, natural language processing, and more. Working remotely, they collaborate with team members via digital tools, write code, optimize models, and often deploy solutions to cloud environments. This role requires strong programming skills, experience with deep learning frameworks (like TensorFlow or PyTorch), and the ability to work independently in a distributed team setting.
What cities in Ohio are hiring for Remote Deep Learning Engineer jobs? Cities in Ohio with the most Remote Deep Learning Engineer job openings:
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.