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Machine Learning Ai Intern Jobs in Louisiana (NOW HIRING)

Ochsner Health

Senior AI Scientists

New Orleans, LA · On-site

Define and evolve Ochsner's artificial intelligence and machine learning (AI/ML) strategy across predictive analytics, generative AI (GenAI/LLMs), Snowflake Cortex capabilities, and Epic ecosystem ...

Ochsner Health

Senior AI Scientists

New Orleans, LA · On-site

Define and evolve Ochsner's artificial intelligence and machine learning (AI/ML) strategy across predictive analytics, generative AI (GenAI/LLMs), Snowflake Cortex capabilities, and Epic ecosystem ...

Spotify

$184K - $262K/yr

Working at the intersection of machine learning, platform engineering, and regulatory compliance ... Find our AI notice here: apply for this job

Pwc

AI Engineer

New Orleans, LA · On-site

$50K - $112K/yr

Certifications aligned to data engineering, machine learning, and cloud platforms, including AWS, Google Cloud, Microsoft Azure, Databricks, Snowflake, or related data and AI credentials - Building ...

COOLSOFT

AI/ML Support Engineer

Baton Rouge, LA · On-site

Tittle : AI/ML Support Engineer Junior Location: Baton Rouge, LA Hybrid, Onsite from Day One ... Support machine learning model development, deployment, and performance optimization . * Analyze ...

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Machine Learning Ai Intern information

What does a Machine Learning AI Intern do?

A Machine Learning AI Intern assists in developing, testing, and deploying machine learning models and algorithms under the supervision of experienced data scientists or engineers. Typical responsibilities include data preprocessing, feature engineering, model evaluation, and documentation. Interns may also help in researching new AI techniques and supporting the integration of models into existing applications. The role provides hands-on experience with machine learning tools, programming languages like Python, and frameworks such as TensorFlow or PyTorch. This internship helps build foundational skills for a career in artificial intelligence and data science.

What types of projects do Machine Learning AI Interns typically work on during their internship?

As a Machine Learning AI Intern, you can expect to work on real-world projects such as developing predictive models, performing data preprocessing and analysis, or contributing to the improvement of existing algorithms. Interns often assist with tasks like data cleaning, feature engineering, and model evaluation, while collaborating closely with data scientists and engineers. This hands-on experience helps interns build practical skills and gain exposure to the entire machine learning workflow in a professional setting.

What are the key skills and qualifications needed to thrive as a Machine Learning AI Intern, and why are they important?

To thrive as a Machine Learning AI Intern, you need a solid foundation in mathematics, programming (often Python), and machine learning concepts, usually supported by coursework or relevant projects. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and version control systems such as Git is typically expected. Curiosity, problem-solving ability, and strong communication skills help interns collaborate effectively and learn quickly in dynamic environments. These skills are crucial for contributing meaningfully to projects, adapting to new technologies, and growing within the fast-evolving AI field.

What is the difference between Machine Learning Ai Intern vs Data Science Intern?

AspectMachine Learning Ai InternData Science Intern
Required CredentialsRelevant coursework, programming skills, basic understanding of ML conceptsStatistics, programming, data analysis skills, often with similar educational background
Work EnvironmentTech companies, startups, research labs focusing on AI/ML projectsVariety of industries including finance, healthcare, tech, focusing on data analysis
Employer & Industry UsagePrimarily in AI/ML development teams within tech and research sectorsAcross industries for data analysis, reporting, and decision-making support

Machine Learning Ai Interns focus on developing and applying AI and ML models, often working closely with data scientists and engineers. Data Science Interns work on analyzing data, creating reports, and supporting data-driven decisions. While both roles require programming and analytical skills, ML Interns typically specialize in AI algorithms, whereas Data Science Interns focus on broader data analysis tasks.

What cities in Louisiana are hiring for Machine Learning Ai Intern jobs?

Cities in Louisiana with the most Machine Learning Ai Intern job openings:

Machine Learning Ai Intern jobs near you

Senior Machine Learning Engineer

Bollinger Shipyards

Raceland, LA • On-site

$99K - $136K/yr

Full-time

Re-posted 7 days ago

Bollinger Shipyards rating

6.5

Company rating: 6.5 out of 10

Based on 10 frontline employees who took The Breakroom Quiz

Job description

Job Title: Senior Machine Learning Engineer
Location: Mulitple Locations
Position Overview:
The Senior ML Engineer is responsible for operationalizing machine learning and AI solutions into scalable, reliable, and production-ready enterprise systems. This role bridges data science, software engineering, and infrastructure disciplines to deploy, monitor, optimize, and support AI solutions that drive operational and business outcomes.
Key Responsibilities:
• Deploy, integrate, and maintain machine learning and AI solutions within enterprise workflows and operational systems
• Design and develop scalable ML pipelines, feature stores, APIs, and model-serving infrastructure
• Collaborate with Data Scientists to productionize models and improve deployment readiness
• Monitor model performance, drift, availability, and reliability across production environments
• Implement processes for model retraining, versioning, governance, and lifecycle management
• Partner with Data Engineering teams to support feature engineering and data pipeline integration
• Ensure ML solutions are secure, scalable, maintainable, and aligned with enterprise architecture standards
• Support AI applications across forecasting, operational optimization, bidding, scheduling, maintenance, and automation use cases
• Troubleshoot and resolve issues related to model deployment and operational performance
• Contribute to ML engineering standards, best practices, and platform improvements
• Document architecture, deployment processes, and operational support procedures
Qualifications:
• Bachelor's degree in Computer Science, Software Engineering, Data Science, or related field
• 6-10 years in ML or software engineering
• Strong Python and ML deployment experience
• Experience with cloud ML systems
Skills:
• Experience with Azure ML, Databricks, ML Ops, or similar cloud AI platforms
• Experience in manufacturing, industrial, operational, or engineering environments
• Familiarity with large language models, Generative AI, and intelligent automation
• Experience supporting enterprise AI applications integrated with ERP or operational systems
• Knowledge of monitoring, observability, and model governance practices
• Experience with Docker, Kubernetes, and infrastructure-as-code practices
Bollinger is an equal opportunity employer and is committed to providing employment opportunities to minorities, females, veterans and disabled individuals, and without regard to sexual orientation and gender identity.

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