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Junior Machine Learning Compiler Engineer Jobs in Florida

Qfanalytics

Machine Learning Engineer

Miami, FL · On-site

$100 - $125/hr

Preferred Qualifications PhD in Mathematics, Engineering, Physics or related field; 4-8 years experience working in Machine Learning; Experience with deep learning frameworks like TensorFlow or ...

Northern Base

Machine Learning Engineer

Sunrise, FL · On-site

$90K - $110K/yr

Role - Machine Learning Engineer Experience Required -8+ Years We are seeking a Machine Learning Engineer to design, build, and deploy Generative AI solutions powered by Large Language Models (LLMs)

ClifyX

Sr. Machine Learning Engineer

Bradenton, FL · On-site

$50.50 - $66.75/hr

ClifyX is seeking a Sr. Machine Learning Engineer who will collaborate with a team of Data ... The role involves designing workflows, developing predictive algorithms, and mentoring junior team ...

Enboarder

Machine Learning Engineer

Boca Raton, FL · On-site

$150 - $200/hr

Summary We are seeking a Machine Learning Engineer to build the "active brain" of our patient engagement platform. In this role, you will develop autonomous and conversational AI agents capable of ...

247Hire

Machine Learning Engineer

Orlando, FL · On-site

$125 - $150/hr

Seeking a Machine Learning Engineer for the following role - Generative AI & ML Frameworks: PyTorch, TensorFlow, Hugging Face Transformers, Diffusers Training: DeepSpeed, Accelerate, Ray, distributed ...

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Junior Machine Learning Compiler Engineer information

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.

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

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

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What job categories do people searching Junior Machine Learning Compiler Engineer jobs in Florida look for?

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What cities in Florida are hiring for Junior Machine Learning Compiler Engineer jobs?

Cities in Florida with the most Junior Machine Learning Compiler Engineer job openings:

Junior Machine Learning Compiler Engineer jobs near you

AI & Machine Learning Engineer

V-Work Infotech Solutions INC

Cape Coral, FL • On-site

Other

This job post has expired today. Applications are no longer accepted.

Job description

Job Summary

We are seeking an experienced AI & Machine Learning Engineer with 10–15+ years of IT experience to design, develop, and deploy scalable AI and machine learning solutions. The ideal candidate will have expertise in Generative AI, Large Language Models (LLMs), deep learning, MLOps, cloud platforms, and production-grade AI systems. You will collaborate with data scientists, software engineers, and business stakeholders to deliver AI-driven products and intelligent automation solutions.

Key Responsibilities
  • Design, develop, and deploy machine learning and Generative AI solutions.
  • Build, fine-tune, and optimize Large Language Models (LLMs) and foundation models.
  • Develop Retrieval-Augmented Generation (RAG) applications.
  • Design AI architectures for enterprise-scale applications.
  • Build end-to-end ML pipelines from data ingestion to model deployment.
  • Develop AI-powered chatbots, virtual assistants, and recommendation systems.
  • Implement prompt engineering techniques to improve LLM performance.
  • Deploy models using MLOps best practices.
  • Optimize model accuracy, latency, scalability, and cost.
  • Work with structured, semi-structured, and unstructured datasets.
  • Collaborate with Data Engineering teams to build scalable AI platforms.
  • Monitor production AI systems and continuously improve model performance.
  • Ensure AI solutions follow security, governance, and responsible AI practices.
  • Mentor junior engineers and provide technical leadership.
Required Qualifications
  • Bachelor''s or Master''s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, or a related field.
  • 10–15+ years of IT experience, with significant experience in AI/ML engineering.
  • Strong understanding of machine learning algorithms, deep learning, and Generative AI.
  • Experience delivering enterprise AI solutions.
  • Excellent communication and problem-solving skills.

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