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Junior Machine Learning Compiler Engineer Jobs in Saint Augustine, FL

Mosai

Machine Learning Operations Engineer

Jacksonville, FL · On-site

$47.50 - $65/hr

Learn more at Position Summary We are seeking an experienced Machine Learning Ops (MLOps) Engineer to architect, develop, and maintain the full lifecycle of data and model pipelines that power ...

Mosai

Machine Learning Operations Engineer

Jacksonville, FL · On-site +1

$47.50 - $65/hr

Learn more at Position Summary We are seeking an experienced Machine Learning Ops (MLOps) Engineer to architect, develop, and maintain the full lifecycle of data and model pipelines that power ...

Varsity Tutors

Machine Learning Tutor

Jacksonville, FL · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

FIS

Data Scientist Sr Lead

Jacksonville, FL · On-site +1

Mentor and develop junior data scientists, fostering a culture of technical excellence, innovation ... machine learning and data engineering. * Own the end-to-end delivery of complex predictive and ...

Worldpay, Inc.

Data Scientist Sr Lead

Jacksonville, FL · On-site +1

Mentor and develop junior data scientists, fostering a culture of technical excellence, innovation ... machine learning and data engineering. * Own the end-to-end delivery of complex predictive and ...

Pwc

CTIO AI Engineering Manager

Jacksonville, FL · On-site

$73K - $244K/yr

Those in data science and machine learning engineering at PwC will focus on leveraging advanced ... junior staff while upholding remarkable standards of quality and innovation in deliverables.

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All JobsMachine Learning Compiler Engineer JobsJunior Machine Learning Compiler Engineer JobsJunior Machine Learning Compiler Engineer Jobs in Saint Augustine, FL

Junior Machine Learning Compiler Engineer information

See Saint Augustine, FL salary details

$29.2K

$62.6K

$95.5K

How much do junior machine learning compiler engineer jobs pay per year?

As of Sep 8, 2026, the average yearly pay for junior machine learning compiler engineer in Saint Augustine, FL is $62,628.00, according to ZipRecruiter salary data. Most workers in this role earn between $42,300.00 and $69,800.00 per year, depending on experience, location, and employer.

What does a junior machine learning compiler engineer do?

A Junior Machine Learning Compiler Engineer helps design, develop, and optimize compilers for machine learning models. Their work involves translating high-level machine learning code into efficient low-level code that can run on various hardware platforms, such as CPUs, GPUs, or specialized AI chips. They often collaborate with software engineers and data scientists to ensure that machine learning workloads run efficiently and correctly. This role typically involves programming, debugging, and performance tuning, often using languages like C++, Python, and specialized frameworks.

What are typical projects and responsibilities for a junior machine learning compiler engineer in a collaborative team setting?

As a Junior Machine Learning Compiler Engineer, you can expect to work on projects that focus on optimizing machine learning models for performance and deployment across various hardware platforms. Typical responsibilities include assisting in developing and debugging compiler passes, implementing optimizations, and contributing to code reviews. You'll frequently collaborate with senior engineers, data scientists, and hardware specialists to ensure that models are efficiently translated and executed. This role offers valuable learning opportunities through hands-on coding, exposure to state-of-the-art ML frameworks, and regular team meetings for knowledge sharing and mentorship.

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

To thrive as a Junior Machine Learning Compiler Engineer, you need a solid background in computer science fundamentals, programming (especially C++ and Python), and foundational knowledge of machine learning and compiler theory. Familiarity with frameworks and tools such as LLVM, TensorFlow, MLIR, and version control systems is typically required, along with a relevant bachelor’s or master’s degree. Strong problem-solving abilities, attention to detail, and effective teamwork and communication skills set standout candidates apart. These skills and qualities are crucial for efficiently optimizing machine learning models for various hardware targets and collaborating on innovative compiler solutions.

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

AspectJunior Machine Learning Compiler EngineerData Scientist
Required CredentialsBachelor's in Computer Science, Software Engineering, or related field; knowledge of compiler design and ML frameworksBachelor's or higher in Data Science, Statistics, Computer Science, or related field; strong analytical skills
Work EnvironmentSoftware development teams, focusing on compiler optimization for ML modelsData analysis teams, focusing on data interpretation and model development
Employer & Industry UsageTech companies, AI startups, hardware firmsTech firms, finance, healthcare, research institutions

The Junior Machine Learning Compiler Engineer primarily focuses on developing and optimizing compilers for machine learning models, requiring programming and compiler knowledge. In contrast, a Data Scientist analyzes data, builds models, and provides insights. Both roles are essential in AI and tech industries but differ in technical focus and daily tasks.

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For Junior Machine Learning Compiler Engineer jobs in Saint Augustine, FL, the most frequently searched job titles are:

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Junior Machine Learning Compiler Engineer jobs near you

Machine Learning Operations Engineer

Mosai

Jacksonville, FL • On-site

$47.50 - $65/hr

Full-time

Posted 11 days ago

Job description

About Mosai
Mosai™ is the intelligent care coordination platform that brings together the fragmented pieces of healthcare into a clear, connected picture. Like a mosaic, our platform unites data, people, and processes so providers can make better decisions, coordinate care in real time, and deliver improved outcomes. With Mosai, home-based care organizations can thrive in value-based care while giving every patient the right care, in the right place, at the right time. Learn more at https://www.mosai.com/
Position Summary
We are seeking an experienced Machine Learning Ops (MLOps) Engineer to architect, develop, and maintain the full lifecycle of data and model pipelines that power training, inference, evaluation, and analytics workflows. This role is responsible for ensuring the reliability, scalability, and observability of all machine learning systems in production, including traditional ML models and modern LLM-based/MCP-orchestrated architectures. A key focus of this role in the near term is auditing and consolidating our existing pipelines and deployment processes. The ideal candidate is highly skilled in Python, Jupyter, Snowflake, and both Azure and AWS cloud environments, and thrives in environments requiring continuous monitoring, rapid issue diagnosis, and rigorous validation before deployment.
Job Duties
  • Design, build, and maintain scalable data pipelines supporting model training, inference, batch processing, and real-time analytics workflows.
  • Audit, refactor, and consolidate existing ML pipelines and deployment processes to eliminate technical debt, redundant workflows, and undocumented manual steps.
  • Audit, refactor, and consolidate existing ML pipelines and deployment processes to eliminate technical debt, redundant workflows, and undocumented manual steps.
  • Monitor and deploy and deploy production ML pipelines to identify anomalies, performance degradations, or failures related to data quality, logic defects, or infrastructure issues.
  • Execute rapid troubleshooting and root-cause analysis followed by timely remediation, validation, and full regression testing prior to redeployment.
  • Collaborate with Data Science, Engineering, and Product teams to operationalize machine learning models-including LLM-based and MCP-orchestrated systems-ensuring seamless integration into production environments.
  • Develop CI/CD workflows, model deployment strategies, and automated testing frameworks to support reliable, repeatable releases.
  • Implement and maintain observability tooling (logging, monitoring, alerting) to ensure high availability and traceability of ML systems.
  • Manage and optimize cloud infrastructure across Azure and AWS for compute, storage, orchestration, and security needs.
  • Create and maintain documentation, runbooks, and best practices for model operations and system maintenance.
  • Perform all other job-related duties as assigned.

Minimum Requirements
  • Bachelor's Degree in Computer Science, Engineering or equivalent work experience.
  • 5-7 years of combined experience in Data Engineering, MLOps, Machine Learning Engineering, or related fields.
  • Demonstrated experience operationalizing traditional ML models as well as LLM-based and MCP-orchestrated systems.
  • Strong working knowledge of both Azure and AWS cloud platforms, including compute orchestration, networking, and security best practices.
  • Experience with CI/CD tools, containerization (Docker), infrastructure-as-code, and ML pipeline frameworks.
  • Strong ability to diagnose and resolve pipeline failures, data anomalies, and complex system issues.

Advanced proficiency in Python, Jupyter, and common ML/analytics frameworks.
  • Hands-on experience with Snowflake or similar cloud data warehousing environment.
  • Excellent problem-solving skills, attention to detail, and a proactive, self-directed work ethic.
  • Strong communication skills and comfort working in fast-paced, cross-functional environments.

Work Environment
  • This role is preferred to be based in Nashville or Jacksonville, near Mosai's offices.

Physical Demands of Our Work Environment
  • This position uses a computer and other office equipment as needed to perform duties. The in-office noise level in the work environment is typical of that of an office. Frequent interruptions may be encountered throughout the workday.
  • The employee is required to either stand or sit, talk and hear frequently required to use repetitive keying or hand motions.
  • The physical demands are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.

Mosai is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, sex, sexual orientation, gender identity, veteran status, and disability, or other legally protected status, If you are unable to submit an application because of a incompatible assistive technology or disability, please contact us at careers@mosai.com. We will make every effort to respond to your request for disability assistance as soon as possible.
Mosai is an E-verify employer. Your eligibility to work in the United States will be verified through the E-verify system if you apply and are selected for a position.

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