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Applied Ai Engineer Jobs in Ohio (NOW HIRING)

United States Digital Space LLC

$120 - $160/hr

RoleAs an Applied AI Engineer, you will turn model capabilities into real product behavior. You will own problems end-to-end, from shaping model behavior, to building the systems around it, to ...

New

home24 SE

$90 - $120/hr

Our new Applied AI Engineer (m/f/d) is a hands‑on technical owner who turns internal stakeholder challenges into reliable production workflows. You combine applied AI engineering, workflow ...

New

Impact.com

Reporting to the Manager of Customer Operations Systems, the Internal Systems Engineer (Applied AI) is a specialized, high-impact builder role dedicated to supercharging our Customer Operations teams ...

Kokosing

Construction AI Engineer

Westerville, OH · On-site

This individual will bridge the gap between software development and practical/applied AI ... The Construction AI Engineer will embody and reinforce the organization's core cultural values ...

Kokosing

Construction AI Engineer

Westerville, OH · On-site

This individual will bridge the gap between software development and practical/applied AI ... The Construction AI Engineer will embody and reinforce the organization's core cultural values ...

The Hartford

Sr AI Machine Learning Engineer

Columbus, OH · Hybrid

$117K - $175K/yr

Sr Data Engineer - GE07BE We're determined to make a difference and are proud to be an insurance ... On the Global Specialty Applied AI team, we utilize the latest AI products and frameworks to ...

Vurvey Labs

AI Software/ Data Engineer

Cincinnati, OH · On-site

$111K - $134K/yr

Vurvey Labs is an applied AI company developing models and platforms that enhance human collaboration. They are seeking a versatile AI Software Engineer to bridge AI initiatives with production ...

KeyCorp

AI-Ready Context Engineer/ Ontologist

Brooklyn, OH · On-site

$96 - $181/hr

The AI-Ready Context Engineer/ Ontologist partners closely with business and technology teams to ... BI), applied AI/ML, and Large Language Model (LLM) use cases. Success in this role requires the ...

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All JobsApplied Ai Engineer JobsApplied Ai Engineer Jobs in Ohio

Applied Ai Engineer information

What are the key skills and qualifications needed to thrive as an applied AI engineer?

To thrive as an Applied AI Engineer, you need strong proficiency in programming (especially Python), machine learning algorithms, statistics, and a relevant degree in computer science or a related field. Familiarity with frameworks like TensorFlow or PyTorch, experience with cloud platforms (such as AWS or Azure), and knowledge of data management tools are typically required. Excellent problem-solving, communication, and teamwork skills help you translate complex models into real-world solutions and collaborate across disciplines. These competencies ensure you can effectively develop, deploy, and maintain AI systems that drive business value.

What are some common challenges applied AI engineers face when deploying AI models into production environments?

Applied AI Engineers often encounter challenges such as ensuring models perform consistently on real-world data, optimizing models for speed and scalability, and integrating AI solutions with existing systems. Managing data privacy, monitoring for model drift, and maintaining robust documentation are also key concerns. Collaboration with DevOps, data engineering, and product teams is essential to address these challenges effectively and deliver reliable AI-driven solutions.

What is the difference between Applied Ai Engineer vs Data Scientist?

AspectApplied Ai EngineerData Scientist
Required CredentialsBachelor's or Master's in CS, AI, or related fields; experience with AI frameworksBachelor's or Master's in CS, Statistics, or related fields; strong analytical skills
Work EnvironmentDevelops and deploys AI models in production environmentsAnalyzes data to extract insights and build predictive models
Industry UsageUsed in tech, healthcare, finance for deploying AI solutionsUsed across industries for data analysis and modeling

Applied Ai Engineers focus on implementing and deploying AI models in real-world applications, while Data Scientists primarily analyze data to generate insights and build predictive models. Both roles require similar educational backgrounds but differ in their core responsibilities and work environments.

How much does an applied AI engineer make?

An applied AI engineer's salary varies based on experience, location, and industry, but typically ranges from $80,000 to $150,000 annually. Senior roles or those with specialized skills in machine learning, deep learning, and programming languages like Python or TensorFlow tend to earn higher salaries.

What does an applied AI engineer do?

An applied AI engineer develops and implements artificial intelligence models and algorithms to solve real-world problems. They work with data, machine learning frameworks, and programming languages like Python or TensorFlow to create practical AI solutions for businesses or products.

What are popular job titles related to Applied Ai Engineer jobs in Ohio?

For Applied Ai Engineer jobs in Ohio, the most frequently searched job titles are:

What job categories do people searching Applied Ai Engineer jobs in Ohio look for?

The top searched job categories for Applied Ai Engineer jobs in Ohio are:

What cities in Ohio are hiring for Applied Ai Engineer jobs?

Cities in Ohio with the most Applied Ai Engineer job openings:

Applied Ai Engineer jobs near you
Infographic showing various Applied Ai Engineer job openings in Ohio as of August 2026, with employment types broken down into 81% Full Time, 17% Part Time, and 2% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution.

Applied AI Engineer

United States Digital Space LLC

On-site

$120 - $160/hr

Other

Posted 2 days ago

New

Job description

About A1There are over 5 billion users using basic applications today such email, notes, tasks that are not AI-native. Our mission is to build a proactive smart assistant for everyday users to bring intelligence to conversations, errands, organising and workflows, with minimal prompting.

Our product focuses on achieving high reliability for long-running workflows, persistent context, and real-world task completion. The system must handle multi-step reasoning, interact with external tools, and remain reliable despite non-deterministic model behavior. Our objective is to help users complete tasks daily enjoyable with over ~90%* reduced time.

RoleAs an Applied AI Engineer, you will turn model capabilities into real product behavior. You will own problems end-to-end, from shaping model behavior, to building the systems around it, to ensuring it performs reliably in production.

This role sits at the intersection of machine learning, systems, and product, focusing on making AI actually work for users, not just in demos, but in real-world usage.

Focus
  • Build and ship AI features end-to-end (model → system → user experience)
  • Design and iterate on prompts, tools, memory, and agent workflows
  • Turn raw model outputs into structured, reliable, and predictable behaviors
  • Debug issues across the full stack (model, orchestration, infra, UX)
  • Optimize for latency, cost, and production reliability
  • Develop lightweight evaluation frameworks to measure real-world performance
  • Work closely with product and engineering to translate ambiguous problems into working systems
Tech Stack
  • PyTorch / JAX
  • LLMs (OpenAI-style APIs, LLaMA, Qwen, etc.)
  • Inference / serving (e.g. vLLM)
  • Vector DB
Ideal Experience
  • Strong foundation in machine learning and modern neural network architectures.
  • Hands-on experience with training, fine-tuning, or deploying ML models
  • Ability to write clean, production-quality code
  • Comfort working across abstraction layers (model → infra → product)
  • Strong problem-solving skills in ambiguous, fast-moving environments
  • Bias toward shipping, iteration, and continuous improvement
Outcomes
  • Production issues are identified quickly, debugged effectively, and root causes addressed.
  • Data pipelines, training loops, and inference systems are robust, reproducible, and maintainable.
  • Collaborates effectively with engineers, product, and research teams to deliver reliable ML-powered features.
  • Iterations on models and systems are driven by real-world signals and measurable improvements.
How We Work

The best products today in the world were built by small, world class teams. We make decisions collectively, move at rapid speed, striking a balance between shipping high quality work and learning. Joining our team requires the ability to bring structure, exercise judgment, and execute independently. Our goal is to put in hands of our users a truly magical AI product.

Interview process

If there appears to be a fit, we'll reach to schedule 3, but no more than 4 interviews.

Applications are evaluated by our technical team members. Interviews will be conducted via virtual meetings and/or onsite.

We value transparency and efficiency, so expect a prompt decision. If you've demonstrated the exceptional skills and mindset we're looking for, we'll extend an offer to join us. This isn't just a job offer; it's an invitation to be part of a team that's bringing AI to have practical benefits to billions globally.

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