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Deep Learning Developer Jobs in Louisiana (NOW HIRING)

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

Must-Have Skills 3+ years of ML engineering experience -- model training, fine-tuning, or post-training pipelines in research or production Strong Python and deep learning proficiency (PyTorch ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Knowledge of deep learning frameworks and methodologies * Experience in applying machine learning ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Knowledge of deep learning frameworks and methodologies * Experience in applying machine learning ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Knowledge of deep learning frameworks and methodologies * Experience in applying machine learning ...

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Deep Learning Developer information

What are the key skills and qualifications needed to thrive as a deep learning developer?

To thrive as a Deep Learning Developer, you need a strong background in computer science, mathematics, and proficiency in programming languages like Python, often supported by a degree in a related field. Familiarity with deep learning frameworks such as TensorFlow or PyTorch, and experience with cloud platforms or GPU acceleration, are commonly required technical skills. Analytical thinking, problem-solving abilities, and effective teamwork distinguish top performers in this role. These competencies are crucial for designing, training, and deploying advanced neural network models that address complex real-world problems.

What is a deep learning developer?

Deep Learning Developers are specialized software engineers or data scientists who design, build, and implement artificial intelligence systems using deep learning techniques. They work with neural networks, large datasets, and various frameworks like TensorFlow or PyTorch to develop models for tasks such as image recognition, natural language processing, and autonomous systems. Their responsibilities include data preprocessing, model training, optimization, and deployment to solve complex problems that require advanced pattern recognition. Deep Learning Developers often collaborate with AI researchers, data engineers, and product teams to integrate intelligent features into applications.

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

AspectDeep Learning DeveloperMachine Learning Engineer
Required CredentialsBachelor's or Master's in CS, AI, or related; experience with neural networksBachelor's or Master's in CS, Data Science, or related; knowledge of algorithms
Work EnvironmentResearch labs, AI startups, tech companies focusing on neural networksData-driven companies, software firms, industries applying machine learning
Industry UsagePrimarily in AI research, neural network development, deep learning projectsBroader application including predictive modeling, data analysis, and ML systems

Deep Learning Developers specialize in neural networks and deep learning models, often working on AI research and complex algorithms. Machine Learning Engineers have a broader focus on developing, deploying, and maintaining machine learning models across various applications. While both roles require similar educational backgrounds, their focus areas and industry applications differ.

What are some common challenges deep learning developers face when deploying models to production environments?

Deep Learning Developers often encounter challenges such as optimizing model performance for real-time inference, managing resource constraints (like GPU/CPU availability), and ensuring model reproducibility across different environments. Additionally, integrating deep learning models into existing software systems and maintaining them over time can be complex, especially as data and requirements evolve. Collaborating closely with DevOps, data engineers, and QA teams is essential to address these challenges and ensure smooth deployment and ongoing reliability.
What cities in Louisiana are hiring for Deep Learning Developer jobs? Cities in Louisiana with the most Deep Learning Developer job openings:
Infographic showing various Deep Learning Developer job openings in Louisiana as of July 2026, with employment types broken down into 1% As Needed, 73% Full Time, 24% Part Time, 1% Temporary, and 1% Contract. Highlights an 86% Physical, 2% Hybrid, and 12% Remote job distribution.

Machine Learning Tutor

Varsity Tutors

New Orleans, LA • Remote

$18 - $40/hr

Part-time

Re-posted 5 days ago


Varsity Tutors rating

5.7

Company rating: 5.7 out of 10

Based on 16 frontline employees who took The Breakroom Quiz

14th of 23 rated private schools and tutoring


Job description

About the Job
The Varsity Tutors Live Learning Platform has thousands of students looking for online Machine Learning tutors nationally. As a tutor on the Varsity Tutors Platform, you'll have the flexibility to set your own schedule, earn competitive rates, and make a real impact on students' academic success and understanding. All from the comfort of your home.
Why Join Our Platform?
  • Earn incrementally higher pay for each session with the same student, reaching up to $40/hour.
  • Get paid up to twice per week, ensuring fast and reliable compensation for the tutoring sessions you conduct and invoice.
  • Set your own hours and tutor as much as you'd like.
  • Tutor remotely using our purpose-built Live Learning Platform. No commuting required.
  • Get matched with students best-suited to your teaching style and expertise.
  • Our AI-powered Tutor Copilot enhances your sessions with real-time instructional support, lesson generation, and engagement features, helping you save prep time and focus on impactful teaching.
  • We handle the logistics—you just invoice for your tutoring sessions, and we take care of payments.

What We Look For In a Machine Learning Tutor
  • Advanced Subject Mastery: Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection, cross-validation, regularization, ensemble methods, dimensionality reduction, clustering, and deep learning fundamentals. Ability to explain linear regression, decision trees, random forests, support vector machines, and neural network architectures while preparing students for data science roles and advanced AI coursework.
  • Conceptual Teaching & Problem-Solving: Skilled at breaking down model training pipelines, hyperparameter tuning, and evaluation metric interpretation. Guides students through data preprocessing, feature selection, building and comparing classification and regression models, implementing clustering algorithms, and interpreting confusion matrices and ROC curves. Emphasizes practical model development workflow and connects machine learning to recommendation systems, fraud detection, and predictive analytics.
  • Curriculum Awareness & Adaptive Instruction: Familiar with machine learning curricula and common challenges such as understanding bias-variance tradeoff, selecting appropriate algorithms for problem types, and interpreting model performance beyond accuracy. Adapts instruction using Python with scikit-learn, Jupyter notebooks, and real-world data sets to support students from introductory statistics-based ML through advanced deep learning and deployment.
  • Effective Teaching Methods: Ability to identify concepts students commonly struggle with, explain material using multiple approaches, and adapt instruction to meet individual learning needs and styles.
  • Strong communication skills and a friendly, engaging teaching style.
  • Ability to adapt to different learning styles and student needs.

Ways To Connect With Students
  • 1-on-1 Online Tutoring - Provide personalized instruction to individual students.
  • Instant Tutoring - Accept on-demand tutoring requests whenever you're available.

About Varsity Tutors And 1-on-1 Online Tutoring
Our mission is to transform the way people learn by leveraging advanced technology, AI, and the latest in learning science to create personalized learning experiences. Through 1-on-1 Online Tutoring, students receive customized instruction that helps them achieve their learning goals. Our platform is designed to match students with the right tutors, fostering better outcomes and a passion for learning.
Please note: Varsity Tutors does not contract in: Alaska, California, Colorado, Delaware, Hawaii, Maine, New Hampshire, North Dakota, Vermont, West Virginia or Puerto Rico.

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