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Remote Machine Learning Compiler Engineer Jobs in Ohio

Digital - Principal SRE

Columbus, OH · On-site +1

$55 - $73.25/hr

Collaborate with cross-functional teams to integrate machine learning models into production ... Remote roles will also have the opportunity to come together in our offices for moments that matter.

Digital - Principal SRE

Columbus, OH · On-site +1

$53.50 - $71.25/hr

Collaborate with cross-functional teams to integrate machine learning models into production ... Remote roles will also have the opportunity to come together in our offices for moments that matter.

AI Engineer

Cincinnati, OH · On-site +1

$109K - $132K/yr

Research, develop, and implement machine learning algorithms and models for tasks such as ... Technical proficiency in programming languages and frameworks commonly used in NLP and AI (e.g ...

Senior AI/ML Engineer

Cincinnati, OH · On-site +1

$100K - $137K/yr

The Senior AI/ML Engineer applies deep expertise in machine learning, applied AI, and creative engineering to ship intelligent, product-driven solutions. This role partners with product, design, and ...

Data Engineer

Cincinnati, OH · On-site +1

$109K - $131K/yr

Support data engineering needs for predictive analytics and machine learning initiatives, including feature engineering, data preparation, and model enablement * Assist in modernizing data platforms ...

New

... machine learning, AI agents, automation, model governance, and responsible AI practices. Daily Activities: • Collaborate with engineering, data science, and design teams to review progress and ...

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.

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.

AI/ML Engineer, Senior

Dayton, OH · On-site +1

$99K - $225K/yr

Remote Work: No Job Number: R0242678 Location: Dayton,OH,US Share job via: Share AI/ML Engineer, Senior The Opportunity: As a Senior Artificial Intelligence and Machine Learning (AI/ML) Engineer, you ...

Monday - Friday 8am - 5pm (Onsite 4 days a week) (Possible remote for the right candidate) Position ... machine learning, or generative AI can improve productivity, reduce cost, or unlock new ...

Monday - Friday 8am - 5pm (Onsite 4 days a week) (Possible remote for the right candidate) Position ... machine learning, or generative AI can improve productivity, reduce cost, or unlock new ...

Showing results 21-40

Remote Machine Learning Compiler Engineer information

What is a remote machine learning compiler engineer?

A Remote Machine Learning Compiler Engineer is a software engineer who specializes in developing and optimizing compilers specifically for machine learning workloads, while working from a remote location. Their primary responsibilities include designing and implementing compiler features that translate machine learning models into efficient code for various hardware platforms, such as CPUs, GPUs, or specialized accelerators. They collaborate closely with machine learning researchers, hardware engineers, and software developers to ensure high performance and compatibility. In addition to strong programming skills, they typically require expertise in compiler theory, machine learning frameworks, and hardware architectures. This role allows for flexible, location-independent work while contributing to cutting-edge AI technologies.

How does a remote machine learning compiler engineer typically collaborate with cross-functional teams to optimize model deployment?

As a Remote Machine Learning Compiler Engineer, you will frequently collaborate with data scientists, hardware engineers, and software developers to ensure that machine learning models are efficiently compiled and deployed on target platforms. Communication often takes place through virtual meetings, code reviews, and shared documentation tools. You'll be responsible for translating research models into optimized code, troubleshooting performance bottlenecks, and integrating feedback from various stakeholders. Effective teamwork is crucial, as the success of deployments often depends on iterative feedback and close alignment with both the ML research and hardware teams.

What are the key skills and qualifications needed to thrive as a remote machine learning compiler engineer, and why are they important?

To thrive as a Remote Machine Learning Compiler Engineer, you need a strong background in computer science, proficiency in programming languages like C++ and Python, and expertise in compiler theory and machine learning frameworks. Familiarity with ML compilers such as TVM or XLA, and experience using version control and CI/CD systems are commonly required, along with a relevant bachelor's or master's degree. Outstanding problem-solving, collaboration, and communication skills are essential for working effectively in distributed teams and across technical domains. These skills and qualities enable the development of efficient, scalable ML solutions that bridge software and hardware, ensuring high performance and innovation.

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

AspectRemote Machine Learning Compiler EngineerRemote Data Scientist
Required CredentialsBachelor's or Master's in Computer Science, Software Engineering, or related fields; knowledge of compiler design and ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in programming, statistics, and data analysis
Work EnvironmentPrimarily software development, compiler optimization, and ML model deploymentData analysis, model building, and interpretation of results
Industry UsageTech companies, AI startups, hardware firms focusing on ML hardware accelerationTech, finance, healthcare, and research organizations

While both roles involve working with machine learning, the Remote Machine Learning Compiler Engineer focuses on developing and optimizing compilers for ML models, whereas the Remote Data Scientist concentrates on analyzing data and building predictive models. The roles share some technical skills but differ in their core responsibilities and work environments.

What are the most commonly searched types of Machine Learning Compiler Engineer jobs in Ohio?

The most popular types of Machine Learning Compiler Engineer jobs in Ohio are:

What cities in Ohio are hiring for Remote Machine Learning Compiler Engineer jobs?

Cities in Ohio with the most Remote Machine Learning Compiler Engineer job openings:

Digital - Principal SRE

Huntington

Columbus, OH • On-site, Remote

$55 - $73.25/hr

Full-time

Re-posted 29 days ago


Job description

Description

The Digital - Principal SRE (AI Engineer) role is a position that blends expertise in artificial intelligence, machine learning, and reliability engineering. This professional is responsible for designing, deploying, and maintaining AI-driven solutions while ensuring the reliability, scalability, and performance of digital platforms and services. The ideal candidate will work closely with Digital SRE engineers, data scientists, DevOps, and operations teams to deliver robust, efficient, and automated systems that support business goals.

Job Description

Summary:

The IS Technical Specialist provides technical and consultative support on the most complex technical matters.This role typically reports to the Head of Digital SRE and may involve on-call responsibilities. The position provides opportunities to work on cutting-edge AI solutions, collaborate with cross segment teams, and drive reliability for mission-critical digital services

Duties and Responsibilities:

  • Design, develop, and implement AI-driven systems and automation tools to enhance the reliability and efficiency of digital platforms.

  • Monitor the health, availability, and performance of AI-enabled applications and infrastructure using SRE best practices.

  • Collaborate with cross-functional teams to integrate machine learning models into production environments, ensuring seamless deployment and operation.

  • Establish and enforce service-level objectives (SLOs), error budgets, and incident response procedures for AI-driven services.

  • Identify, troubleshoot, and resolve complex incidents related to AI systems, leveraging observability and monitoring tools.

  • Drive continuous improvement by analyzing post-incident reviews, automating manual tasks, and optimizing system performance.

  • Stay up to date with advancements in AI, SRE, and cloud technologies, recommending innovative solutions to enhance digital reliability.

  • Document processes and runbooks for operational transparency and knowledge sharing.

  • AI Platform Integration: Develop abstraction layers across AI providers (Google, OpenAI, etc. ) to enable seamless integration and enablement.

  • Conduct design workshops, POCs, and code-with sessions to shape data-driven agent workflows with stakeholders, fostering trust and adoption.

  • Measure & Improve: Define and use key metrics, test harnesses, and evaluation plans to measure agent accuracy, latency, safety, and cost effectiveness.

  • Knowledge Sharing: Craft reusable patterns, documentation, and best practices to influence internal assets and client roadmaps.

Basic Qualifications:

  • Bachelor's or master's degree in computer science, Engineering, Data Science, or a related field.
  • Minimum 5 YOE Proven experience in AI/ML engineering, SRE, DevOps, or related roles.
  • Strong programming skills in Python, Java, or similar languages, with experience in developing and deploying machine learning models.
    • Hands-on experience with cloud platforms (e.g., AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes).
    • Familiarity with observability tools (Prometheus, Grafana, ELK stack) and Service Now incident management platforms.
    • Solid understanding of SRE principles: monitoring, alerting, SLOs, error budgets, and automation.
    • Experience with infrastructure-as-code (Terraform, Ansible) and CI/CD pipelines.
    • Excellent problem-solving skills, attention to detail, and ability to work in a fast-paced, collaborative environment.

Preferred Qualifications:

  • Experience operationalizing large language models (LLMs) or generative AI systems in production settings.

  • Background in MLOps, data engineering, and/or cloud-native AI deployment.

  • Strong communication and documentation abilities

  • Knowledge of security best practices for AI and cloud infrastructure.

  • Contributions to open source AI/SRE projects or relevant technical communities


Exempt Status: (Yes= not eligible for overtime pay) (No= eligible for overtime pay)

Yes

Workplace Type:

Office

Our Approach to Office Workplace Type

Certain positions outside our branch network may be eligible for a flexible work arrangement. We're combining the best of both worlds: in-office and work from home. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. Remote roles will also have the opportunity to come together in our offices for moments that matter. Specific work arrangements will be provided by the hiring team.

Huntington is an Equal Opportunity Employer.

Tobacco-Free Hiring Practice: Visit Huntington's Career Web Site for more details.

Note to Agency Recruiters: Huntington Bank will not pay a fee for any placement resulting from the receipt of an unsolicited resume. All unsolicited resumes sent to any Huntington Bank colleagues, directly or indirectly, will be considered Huntington Bank property. Recruiting agencies must have a valid, written and fully executed Master Service Agreement and Statement of Work for consideration.