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Remote Machine Learning Compiler Engineer Jobs in Ohio

Data Solutions Engineer

Cincinnati, OH · On-site +1

$91K - $156K/yr

Stay abreast of the latest trends in cloud computing, machine learning, AI, and data engineering. Explore new technologies and methodologies to continuously improve systems, tools, and data processes.

AI Engineer

Cincinnati, OH · On-site +1

$101K - $159K/yr

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

... 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 ...

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 ...

SENIOR DATA ARCHITECT - DIGITAL HEALTH

Dayton, OH · On-site +1

$65.25 - $87.50/hr

... programming (Python/Scala) * Experience with Azure ecosystem, preferable * Knowledge of Linux OS * Familiarity with machine learning and data science concepts Benefits * Fully Remote work-from-home ...

SENIOR DATA ARCHITECT - DIGITAL HEALTH

Dayton, OH · On-site +1

$65.25 - $87.50/hr

... programming (Python/Scala) * Experience with Azure ecosystem, preferable * Knowledge of Linux OS * Familiarity with machine learning and data science concepts Benefits * Fully Remote work-from-home ...

Senior Data Engineer

Cleveland, OH · On-site +1

$102K - $139K/yr

* Experience: 8-10 years in Data Engineering and Data Analysis. * Informatica Expertise: Strong hands ... Familiarity with machine learning models and AI concepts. * Experience with data modeling tools ...

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Remote Machine Learning Compiler Engineer information

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 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.

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 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 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 job categories do people searching Remote Machine Learning Compiler Engineer jobs in Ohio look for? The top searched job categories for Remote 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:

AI Engineer/ML Engineer - Senior Developers - AI Training - Columbus, US

Prolific Academic Ltd

Columbus, OH • On-site, Remote

$80/hr

Full-time

Posted 27 days ago

Be an early applicant


Job description

AI & Machine Learning Engineer - AI TrainingAbout Prolific

Prolific is not just another player in the AI space – we are building the biggest pool of quality human data in the world.

Over 35,000 AI developers, researchers, and organizations use Prolific to gather data from paid study participants with a wide variety of experiences, knowledge, and skills.

The role

We're looking for AI and Machine Learning Engineers to join our Expert Network to help train and evaluate the next generation of LLMs using deep technical expertise. If you have the necessary experience, we'll send you a quick 10- to 15-minute test to assess your skills and suitability for AI tasks. If successful, you'll be invited to join Prolific as a participant, where you'll get paid to train and evaluate powerful AI models.

Researchers looking for your skills tend to pay up to $80 per hour. You must be prepared to complete paid tasks that require one hour of uninterrupted work, though many are shorter.

What you'll bring
  • Education: a BS, MS, or PhD in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field with a focus on Machine Learning.
  • Professional Experience: experience building, deploying, or fine-tuning ML models in a production environment.
  • Deep Learning Mastery: professional-level understanding of neural network architectures (Transformers, CNNs, RNNs) and optimization techniques.
  • LLM Specialization: hands-on experience with Prompt Engineering, RLHF (Reinforcement Learning from Human Feedback), or RAG (Retrieval-Augmented Generation) workflows.
  • Technical Rigor: the ability to audit complex model logic, identify training data contamination, and evaluate mathematical proofs behind ML algorithms.
  • Analytical Critique: high attention to detail in spotting "hallucinations," biased outputs, or logical failures in AI-generated technical content.
What you'll be doing in the role
  • Evaluate LLM Architecture Logic: review AI-generated explanations of model architectures, loss functions, and backpropagation for technical accuracy.
  • Audit Code & Notebooks: validate ML-specific code (e.g., training loops, data preprocessing scripts, or model evaluations) for efficiency and correctness.
  • Refine RLHF Frameworks: provide the high-quality human feedback necessary to align models with human intent, safety, and helpfulness.
  • Analyze Model Reasoning: critically assess how an AI model navigates complex chain-of-thought (CoT) prompts and identify where the reasoning breaks down.
  • Benchmark Performance: conduct comparative testing between different model outputs based on specific technical taxonomies and performance metrics.
Key Technologies
  • Frameworks: expert proficiency in PyTorch or TensorFlow/Keras.
  • Language & Data: advanced Python (NumPy, Pandas, Scikit-learn) and experience with Hugging Face Transformers.
  • Cloud & MLOps: experience with AWS (SageMaker), Google Cloud (Vertex AI), or specialized tools like Weights & Biases and LangChain.
  • Vector Databases: familiarity with Pinecone, Milvus, or Weaviate for RAG evaluation.
Why Prolific is a great platform to join as a Participant

Joining our Expert Network will give you the chance to influence the AI models of the future using professional legal expertise. Once you pass our assessment, you can join Prolific in just 15 minutes, and start enjoying competitive pay rates, flexible hours, and the ability to work from home.

We've built a unique platform that connects researchers and companies with a global pool of participants, enabling the collection of high-quality, ethically sourced human behavioural data and feedback. This data is the cornerstone of developing more accurate, nuanced, and aligned AI systems.

We believe that the next leap in AI capabilities won't come solely from scaling existing models, but from integrating diverse human perspectives and behaviours into AI development. By providing this crucial human data infrastructure, Prolific is positioning itself at the forefront of the next wave of AI innovation – one that reflects the breadth and the best of humanity.
Links to more information on Prolific

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Privacy Statement

By submitting your application, you agree that Prolific may collect your personal data for recruiting and global organisation planning. Prolific's Candidate Privacy Notice explains what personal information Prolific may process, where Prolific may process your personal information, its purposes for processing your personal information, and the rights you can exercise over Prolific use of your personal personal information.