Expert-level proficiency in Python and relevant libraries (e.g., FastAPI, Pydantic, PyTorch, HuggingFace Ecosystem). • Experience with LLM-based pipelines: Proven experience in building and ...
Expert-level proficiency in Python and relevant libraries (e.g., FastAPI, Pydantic, PyTorch, HuggingFace Ecosystem). • Experience with LLM-based pipelines: Proven experience in building and ...
Scikit-learn, TensorFlow, Keras, PyTorch, HuggingFace Transformers, OpenCV, NLTK and BART * Understanding of RAG architectures, embeddings, and semantic search (bonus). GenAI & AI Agent Development
Scikit-learn, TensorFlow, Keras, PyTorch, HuggingFace Transformers, OpenCV, NLTK and BART * Understanding of RAG architectures, embeddings, and semantic search (bonus). GenAI & AI Agent Development
Hands-on experience with any major deep learning framework and libraries (TensorFlow, TensorRT, PyTorch, or HuggingFace) * Hands-on experience with MLOps and CI/CD toolset including MLFlow, WandB ...
Hands-on experience with any major deep learning framework and libraries (TensorFlow, TensorRT, PyTorch, or HuggingFace) * Hands-on experience with MLOps and CI/CD toolset including MLFlow, WandB ...
Hands-on experience with ML frameworks such as PyTorch, TensorFlow, HuggingFace Transformers, or LangChain. * Deep knowledge of GenAI techniques including prompt engineering, RAG pipelines, LLM ...
Hands-on experience with ML frameworks such as PyTorch, TensorFlow, HuggingFace Transformers, or LangChain. * Deep knowledge of GenAI techniques including prompt engineering, RAG pipelines, LLM ...
Cleared AI/ML Engineer
Tampa, FL · On-site
$108K - $185K/yr
Hands-on experience with any major deep learning framework and libraries (TensorFlow, TensorRT, PyTorch, or HuggingFace) * Hands-on experience with MLOps and CI/CD toolset including MLFlow, WandB ...
Cleared AI/ML Engineer
Tampa, FL · On-site
$108K - $185K/yr
Hands-on experience with any major deep learning framework and libraries (TensorFlow, TensorRT, PyTorch, or HuggingFace) * Hands-on experience with MLOps and CI/CD toolset including MLFlow, WandB ...
Cleared AI/ML Engineer
$108K - $185K/yr
Hands-on experience with any major deep learning framework and libraries (TensorFlow, TensorRT, PyTorch, or HuggingFace) * Hands-on experience with MLOps and CI/CD toolset including MLFlow, WandB ...
Cleared AI/ML Engineer
$108K - $185K/yr
Hands-on experience with any major deep learning framework and libraries (TensorFlow, TensorRT, PyTorch, or HuggingFace) * Hands-on experience with MLOps and CI/CD toolset including MLFlow, WandB ...
Cleared AI/ML Engineer
$108K - $185K/yr
Hands-on experience with any major deep learning framework and libraries (TensorFlow, TensorRT, PyTorch, or HuggingFace) * Hands-on experience with MLOps and CI/CD toolset including MLFlow, WandB ...
Cleared AI/ML Engineer
$108K - $185K/yr
Hands-on experience with any major deep learning framework and libraries (TensorFlow, TensorRT, PyTorch, or HuggingFace) * Hands-on experience with MLOps and CI/CD toolset including MLFlow, WandB ...
Pytorch Huggingface information
What are the key skills and qualifications needed to thrive as a PyTorch Hugging Face Engineer, and why are they important?
To thrive as a PyTorch Hugging Face Engineer, you need a strong background in deep learning, Python programming, and experience with machine learning frameworks, supported by a relevant degree such as computer science or engineering. Familiarity with PyTorch, Hugging Face Transformers library, version control systems like Git, and often cloud platforms (e.g., AWS, GCP) is essential, with certifications in machine learning or cloud technologies being advantageous. Strong problem-solving skills, collaboration, and clear communication help you effectively design, implement, and optimize NLP models in cross-functional teams. These skills ensure you can build state-of-the-art AI solutions efficiently, troubleshoot complex challenges, and deliver impactful results in the fast-evolving field of natural language processing.
What is the difference between Pytorch Huggingface vs Machine Learning Engineer?
| Aspect | Pytorch Huggingface | Machine Learning Engineer |
|---|---|---|
| Credentials | Proficiency in Python, deep learning frameworks, familiarity with NLP libraries | Degree in CS, data science, or related field; experience with ML models |
| Work Environment | Research labs, AI startups, tech companies focusing on NLP and deep learning | Tech companies, consulting firms, R&D departments across industries |
| Usage | Developing NLP models, fine-tuning transformers, deploying AI solutions | Designing, building, and deploying ML models across various domains |
While Pytorch Huggingface specializes in NLP model development using transformer architectures, Machine Learning Engineers work across diverse ML applications. Pytorch Huggingface skills are often part of a Machine Learning Engineer's toolkit, but the roles differ in scope and focus.
What are Pytorch Huggingface developers?
PyTorch Hugging Face developers are professionals who specialize in building and deploying machine learning and natural language processing (NLP) models using PyTorch, an open-source deep learning framework, and the Hugging Face library, which provides a wide range of pre-trained models and tools for NLP tasks. These developers create, fine-tune, and implement models for tasks like text classification, question answering, and language generation. Their expertise includes working with model architectures such as BERT, GPT, and others, as well as integrating models into applications or research projects.
How do PyTorch Huggingface engineers typically collaborate with data scientists and researchers in a project setting?
PyTorch Huggingface engineers often work closely with data scientists and researchers to implement, fine-tune, and deploy state-of-the-art machine learning models. Collaboration involves regular discussions to understand project objectives, translating research ideas into efficient code, and iterating on model performance. Engineers are responsible for optimizing model pipelines, integrating new features, and ensuring compatibility with the Huggingface ecosystem. Effective communication and teamwork are essential, as projects usually require frequent feedback loops and joint problem-solving sessions.
What are popular job titles related to Pytorch Huggingface jobs in Florida? For Pytorch Huggingface jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Pytorch Huggingface jobs in Florida look for? The top searched job categories for Pytorch Huggingface jobs in Florida are:
What cities in Florida are hiring for Pytorch Huggingface jobs? Cities in Florida with the most Pytorch Huggingface job openings:
Full-time
Posted 12 days ago
Job description
Role: Senior Full Stack AI Engineer
Location: Tampa, FL (3 Days onsite/ week)
Fulltime
Requirements:
• Extensive Experience: Minimum of 5 years of proven software development experience.
• Modern Application Development:
• In-depth knowledge of modern application architecture principles.
• Clear understanding of Data Structures and Object Oriented Principles
• Practical experience with Artificial Intelligence (AI) tools for enhancing development workflows.
• Proficiency in Microservices frameworks Event-Driven Services, and Cloud-Native Application
Development.
• Multiple years of experience on Service Oriented and Microservices architectures, including
REST and GraphQL implementations
• Strong Python Engineering: Expert-level proficiency in Python and relevant libraries (e.g.,
FastAPI, Pydantic, PyTorch, HuggingFace Ecosystem).
• Experience with LLM-based pipelines: Proven experience in building and deploying applications
using Large Language Models.
• Knowledge of vector search and embeddings: Hands-on experience with vector databases and
developing embedding pipelines.
• RAG Concepts: Strong understanding and practical experience with Retrieval-Augmented
Generation (RAG) frameworks (e.g., LangChain, LlamaIndex).
• GenAI Tuning: Experience with generative AI tuning techniques such as QLORA, LORA, and PEFT.
• MCP Experience: Practical experience with Agentic Workflows, and Model Context Protocol
(MCP) for enhancing development workflows
• NLP Expertise: Strong hands-on experience with NLP techniques such as text classification,
summarization, and topic modeling.
• Full Stack Proficiency: Demonstrated ability to design, develop, and maintain both front-end and back-
end components of robust web applications.
Personal - Individual Use
• Front-End Development: Strong expertise in developing intuitive user interfaces using contemporary
JavaScript frameworks (e.g., React), HTML5, and CSS.
• Back-End Development: Solid experience in developing server-side logic and APIs using languages
Python, Java, or similar.
• Database Expertise: Comprehensive knowledge of SQL and PL/SQL, with a deep understanding of
Relational Database Management Systems (RDBMS), particularly Oracle.
• API Development: Proven capability in designing, developing, and implementing high-performance
RESTful APIs leveraging appropriate frameworks and technologies.
• CI/CD and DevOps:
• Proficiency with Continuous Integration/Continuous Deployment (CI/CD) pipelines and tools for
building (e.g., Maven, Gradle) and deploying code (e.g., Docker, Jenkins, OpenShift).
• Experience with AWS is considered a significant advantage.
• Agile Methodologies: Practical experience working within Agile development methodologies and utilizing
project management tools such as JIRA.
• Testing Automation: Ability to develop and automate comprehensive unit, integration, and end-to-end
tests to ensure code quality.
• Version Control: Solid understanding and practical experience with code versioning tools, including
GitHub Enterprise.
Location: Tampa, FL (3 Days onsite/ week)
Fulltime
Requirements:
• Extensive Experience: Minimum of 5 years of proven software development experience.
• Modern Application Development:
• In-depth knowledge of modern application architecture principles.
• Clear understanding of Data Structures and Object Oriented Principles
• Practical experience with Artificial Intelligence (AI) tools for enhancing development workflows.
• Proficiency in Microservices frameworks Event-Driven Services, and Cloud-Native Application
Development.
• Multiple years of experience on Service Oriented and Microservices architectures, including
REST and GraphQL implementations
• Strong Python Engineering: Expert-level proficiency in Python and relevant libraries (e.g.,
FastAPI, Pydantic, PyTorch, HuggingFace Ecosystem).
• Experience with LLM-based pipelines: Proven experience in building and deploying applications
using Large Language Models.
• Knowledge of vector search and embeddings: Hands-on experience with vector databases and
developing embedding pipelines.
• RAG Concepts: Strong understanding and practical experience with Retrieval-Augmented
Generation (RAG) frameworks (e.g., LangChain, LlamaIndex).
• GenAI Tuning: Experience with generative AI tuning techniques such as QLORA, LORA, and PEFT.
• MCP Experience: Practical experience with Agentic Workflows, and Model Context Protocol
(MCP) for enhancing development workflows
• NLP Expertise: Strong hands-on experience with NLP techniques such as text classification,
summarization, and topic modeling.
• Full Stack Proficiency: Demonstrated ability to design, develop, and maintain both front-end and back-
end components of robust web applications.
Personal - Individual Use
• Front-End Development: Strong expertise in developing intuitive user interfaces using contemporary
JavaScript frameworks (e.g., React), HTML5, and CSS.
• Back-End Development: Solid experience in developing server-side logic and APIs using languages
Python, Java, or similar.
• Database Expertise: Comprehensive knowledge of SQL and PL/SQL, with a deep understanding of
Relational Database Management Systems (RDBMS), particularly Oracle.
• API Development: Proven capability in designing, developing, and implementing high-performance
RESTful APIs leveraging appropriate frameworks and technologies.
• CI/CD and DevOps:
• Proficiency with Continuous Integration/Continuous Deployment (CI/CD) pipelines and tools for
building (e.g., Maven, Gradle) and deploying code (e.g., Docker, Jenkins, OpenShift).
• Experience with AWS is considered a significant advantage.
• Agile Methodologies: Practical experience working within Agile development methodologies and utilizing
project management tools such as JIRA.
• Testing Automation: Ability to develop and automate comprehensive unit, integration, and end-to-end
tests to ensure code quality.
• Version Control: Solid understanding and practical experience with code versioning tools, including
GitHub Enterprise.