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Remote Deep Learning Engineer Jobs in Ohio (NOW HIRING)

Paychex

AI Engineer

Cincinnati, OH · On-site +1

$124K - $160K/yr

Overview The AI Engineer will play a crucial role in developing and implementing artificial ... Design, develop, and implement machine learning and deep learning models to address various ...

Eliassen Group

Senior AI/ML Engineer

Columbus, OH · Remote

$90 - $100/hr

Remote Our client seeks a Senior AI/ML Engineer to design and deliver cloud-native machine learning ... For nearly 40 years, we have combined exceptional people, deep domain expertise, and intelligent ...

Penske

Staff Data Scientist

Beachwood, OH · On-site +1

Monday - Friday 8am - 5pm (Onsite 4 days a week) (Possible remote for the right candidate) Position ... deep learning, and NLP. * Familiarity with generative AI and LLMs, including prompt engineering ...

Penske

Staff Data Scientist

Beachwood, OH · On-site +1

Monday - Friday 8am - 5pm (Onsite 4 days a week) (Possible remote for the right candidate) Position ... deep learning, and NLP. * Familiarity with generative AI and LLMs, including prompt engineering ...

Paychex

AI Engineer

Cincinnati, OH · On-site +1

$101K - $159K/yr

... deep learning models. Ability to build and deploy MCP servers to provide LLMs with secure ... remote tools.. * Applicant should have experience in infrastructure disciplines of networking ...

Penske

Staff Data Scientist

Beachwood, OH · On-site +1

Monday - Friday 8am - 5pm (Onsite 4 days a week) (Possible remote for the right candidate)   ... deep learning, and NLP. Familiarity with generative AI and LLMs, including prompt engineering ...

84.51°

Lead Software Engineer

Cincinnati, OH · Remote

... GenAI and deep learning methods * Professional experience with AI/ML frameworks and tooling ... Remote Pay Transparency and Benefits * The stated salary range represents the entire span ...

Huntington

Senior Data Scientist - AI

Columbus, OH · On-site +1

Determines requirements that will be used to train and evolve deep learning models and algorithms ... 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

Determines requirements that will be used to train and evolve deep learning models and algorithms ... Remote roles will also have the opportunity to come together in our offices for moments that matter.

Huntington

Senior Data Scientist

Columbus, OH · On-site +1

Determines requirements that will be used to train and evolve deep learning models and algorithms ... Remote roles will also have the opportunity to come together in our offices for moments that matter.

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Showing results 1-20

All JobsRemote Deep Learning Engineer JobsRemote Deep Learning Engineer Jobs in Ohio

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 Jun 18, 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 are popular job titles related to Remote Deep Learning Engineer jobs in Ohio? For Remote Deep Learning Engineer jobs in Ohio, the most frequently searched job titles are:
What job categories do people searching Remote Deep Learning Engineer jobs in Ohio look for? The top searched job categories for Remote Deep Learning Engineer jobs in Ohio are:
What cities in Ohio are hiring for Remote Deep Learning Engineer jobs? Cities in Ohio with the most Remote Deep Learning Engineer job openings:
Remote Deep Learning Engineer jobs near you
Distinguished AI/ML Engineering Lead

Distinguished AI/ML Engineering Lead

Frontier Technology Inc.

Dayton, OH • Remote

$99K - $131K/yr

Full-time

Posted 11 days ago

Job description

Overview

FTI Defense delivers mission-focused solutions to the Department of Defense and Intelligence Community through advanced engineering, digital transformation, and program execution expertise. We help our customers solve complex challenges and achieve mission success by integrating people, process, and technology.

FTI Defense is seeking a Distinguished AI/ML Engineer to serve as a technical leader, architect, and integrator - designing, building, deploying, and sustaining AI systems that transform complex mission data into trusted, explainable insights.

This is a hands-on builder role, not an analytics management position. The ideal candidate is equally comfortable writing model code, standing up ML pipelines, and integrating AI inference services into operational systems within secure environments. The right candidate blends deep AI/ML engineering expertise with system-level architecture leadership and an ability to unify data engineering, simulation modeling, and responsible AI principles into scalable, mission-ready capabilities.

Responsibilities
  • Architect and integrate hybrid AI systems that combine traditional machine learning, deep learning, large language models (LLMs), and retrieval-augmented generation (RAG) pipelines.
  • Design and deploy scalable AI architectures including APIs, microservices, and model-serving frameworks that integrate seamlessly with analytic, simulation, or operational systems.
  • Lead the full AI/ML lifecycle - from data ingestion and feature engineering through training, deployment, and sustainment within secure DoD environments (IL5/IL6, ATO, GovCloud).
  • Engineer event-driven data pipelines and feature stores for both structured and unstructured data, including text, imagery, and simulation outputs.
  • Ensure Responsible AI practices by embedding traceability, explainability, and confidence scoring into deployed systems.
  • Implement and maintain MLOps pipelines (MLflow, Kubeflow, Airflow, Docker/Kubernetes) to support continuous integration, retraining, and drift detection.
  • Transition R&D prototypes into production, optimizing for mission constraints such as limited compute, edge environments, or disconnected operations.
  • Provide technical leadership and mentorship, setting standards for model quality, architectural design, and ethical AI deployment across programs.
  • Collaborate across engineering, data, and modeling teams to unify FTI's AI portfolio, ensuring interoperability and reuse across mission systems.
  • Support proposal and solution development, providing technical inputs for AI/ML architectures, data strategies, and Responsible AI assurance frameworks.
Education/Qualifications
  • Active Secret clearance required; TS/SCI strongly preferred.
  • Bachelor's degree in Computer Science, Engineering, or a related technical field (Master's or Ph.D. preferred).
  • 10+ years of overall experience in AI/ML development, with 5+ years designing and deploying scalable AI/ML architectures, including at least two full lifecycle implementations (from prototype to operational system).
  • Proficiency in Python, PyTorch, TensorFlow, and modern ML frameworks.
  • Experience designing or deploying systems using vector databases (Milvus, Pinecone, Weaviate), knowledge graphs, and semantic search frameworks.
  • Proven ability to design event-driven data pipelines using Databricks, Spark, Flink, or Kafka.
  • Demonstrated experience deploying AI/ML systems in secure, classified, or edge environments.
  • Familiarity with Responsible AI and assurance principles, including bias detection, explainability, human-machine teaming, and hallucination prevention.
  • Experience integrating AI models into simulation, modeling, or operational planning systems is highly desirable.
  • Experience transitioning R&D systems into accredited production environments.
  • Strong communication and mentoring skills, with the ability to lead technically while remaining deeply hands-on.

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Employment Type: FULL_TIME

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