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Pytorch Developer Jobs in Florida (NOW HIRING)

Data Engineer

Davie, FL · On-site

$104K - $126K/yr

Data Engineer (Core Data Engineer role) 1 year assignment.(Temp to perm: Based on openings and ... Experience with machine learning frameworks like TensorFlow or PyTorch. Education: Minimum Master ...

Experience with deep learning frameworks (e.g., PyTorch, TensorFlow, Keras). * Familiarity with AI ... Python programming * Natural Language Processing (NLP) * Agentic AI, including LangChain, LangGraph ...

Sr Gen AI Engineer

Delray Beach, FL · On-site

$87K - $140K/yr

Create developer tools and frameworks that enable internal teams to leverage AI capabilities ... Experience with machine learning frameworks such as PyTorch, TensorFlow, or JAX * Familiarity with ...

Software Engineer Location: Riviera Beach, FL Plans, conducts, and coordinates software development ... Machine Learning-Neural Networsk (Keras, Theano,Tensorflow, PyTorch and Caffe) Must be US citizen ...

... PyTorch (TensorFlow experience acceptable) • Airflow for job orchestration, particularly managing resources between training and inference workloads • Strong Kubernetes experience including ...

... PyTorch (or similar). About Citadel Securities Citadel Securities is a technology-driven, next ... Our teams of engineers, traders and researchers harness leading-edge quantitative research and the ...

The role is for an AI Engineer focused on designing, developing, and implementing machine learning ... Experience with machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn. * Knowledge ...

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Pytorch Developer information

What is a PyTorch Developer?

A PyTorch Developer is a software engineer or data scientist who specializes in using PyTorch, an open-source machine learning library, to build and deploy deep learning models. Their responsibilities typically include designing neural network architectures, training and evaluating models, and optimizing code for performance. PyTorch Developers work in fields such as artificial intelligence, computer vision, and natural language processing, collaborating with teams to solve complex problems using machine learning. They are proficient in Python and have a strong understanding of deep learning concepts. Additionally, they often contribute to research, development, and the deployment of AI solutions in production environments.

What are the key skills and qualifications needed to thrive as a Pytorch Developer, and why are they important?

To thrive as a Pytorch Developer, you need strong programming skills in Python, a solid grasp of machine learning concepts, and experience with deep learning frameworks—especially PyTorch itself. Familiarity with tools like CUDA, Jupyter Notebooks, and version control systems (e.g., Git) is typically expected, along with knowledge of cloud platforms or relevant certifications. Problem-solving ability, effective collaboration, and clear communication are crucial soft skills for success in this role. These skills and qualities are vital for efficiently building, optimizing, and deploying machine learning models in real-world applications.

What is the difference between Pytorch Developer vs Machine Learning Engineer?

AspectPytorch DeveloperMachine Learning Engineer
Required CredentialsBachelor's or higher in CS, experience with PyTorchBachelor's or higher in CS, data science, or related field, with ML experience
Work EnvironmentResearch labs, AI startups, tech companies focusing on deep learningTech companies, finance, healthcare, often involving deployment and scaling ML models
Industry UsagePrimarily in AI research and development teamsAcross industries implementing ML solutions in production

While both roles require knowledge of machine learning and experience with PyTorch, a Pytorch Developer mainly focuses on developing and optimizing deep learning models using PyTorch. A Machine Learning Engineer often has a broader scope, including deploying, maintaining, and scaling ML models across various platforms and industries.

What are some common challenges Pytorch Developers face when deploying machine learning models to production environments?

Pytorch Developers often encounter challenges when transitioning models from research to production, such as optimizing model performance for inference speed and memory usage, ensuring compatibility with deployment frameworks like TorchScript or ONNX, and managing dependencies across different systems. Additionally, integrating PyTorch models into existing software stacks and maintaining reproducibility can be complex. Collaborating closely with DevOps and data engineering teams is crucial to address these issues and ensure smooth deployment.
What cities in Florida are hiring for Pytorch Developer jobs? Cities in Florida with the most Pytorch Developer job openings:
Data Engineer

Data Engineer

Unicon Pharma Inc.

Davie, FL • On-site

$104K - $126K/yr

Contractor

Posted 29 days ago


Job description

Description:
Title: Data Engineer (Core Data Engineer role)
1 year assignment.(Temp to perm: Based on openings and performance)
Davie, FL (Onsite)

Shift: Monday - Friday 8:00am - 5:00pm, 40 hours a week
Core Essential skill sets candidates must have:
1. Min 3 years experience as an expert using Power BI. Looking for persons who have created presentations and Dashboards. We are not looking for someone who has worked with a team to create these as a team but we are needing someone who knows how to create as aspects of the presentations and dashboard on their own.
2. Must be certified with Power BI Fabric.
3. Must have experience using Power BI creating models and dashboards. (Power BI fabrics & semantic models.)
4. Must have PL300 & Python certifications.
5. Must have experience using Power BI in Pharmaceutical Industry. (The worker must have good understanding of the Pharmaceutical industry.)
6. Proficiency in programming languages such as Python, R, and SQL. Experience with machine learning frameworks like TensorFlow or PyTorch.
Education:
Minimum Master's in Data Science and Compute Science - Graduate in recent years
Job Description:
a. Data Analysis: Analyze large datasets from manufacturing processes to derive actionable insights.
b. Predictive Modeling: Develop and implement predictive models to define process performance.
c. Collaboration: Work closely with cross-functional teams, including chemists, engineers, etc., to support data-driven decision-making.
d. Machine Learning: Apply machine learning algorithms to optimize process development and manufacturing processes.
e. Data Visualization: Create visualizations to communicate findings to stakeholders and support strategic planning.