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Internship Machine Learning Quant Jobs in Alabama

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Internship Machine Learning Quant information

What is the difference between Internship Machine Learning Quant vs Data Scientist Intern?

AspectInternship Machine Learning QuantData Scientist Intern
Required CredentialsStrong programming skills, basic finance knowledge, coursework in machine learningStatistics, programming, domain knowledge, coursework in data analysis
Work EnvironmentFinancial firms, hedge funds, quantitative trading teamsTech companies, startups, research labs
Industry UsageFinance, trading, quantitative researchTechnology, marketing, healthcare analytics
Common Search IntentInternship roles in finance with machine learning focusInternship roles in data science across industries

Internship Machine Learning Quant roles typically focus on applying machine learning techniques to financial data within trading and investment firms. Data Scientist Intern positions are broader, spanning various industries like tech and healthcare, emphasizing data analysis and modeling. While both require programming and analytical skills, the finance-specific knowledge is more critical for Machine Learning Quant internships.

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What job categories do people searching Internship Machine Learning Quant jobs in Alabama look for? The top searched job categories for Internship Machine Learning Quant jobs in Alabama are:
What cities in Alabama are hiring for Internship Machine Learning Quant jobs? Cities in Alabama with the most Internship Machine Learning Quant job openings:
Internship Machine Learning Quant jobs near you

Machine Learning Engineer (TS/SCI)

Search Tactics LLC

Huntsville, AL • On-site

Other

Posted 6 days ago

Job description

Title: Machine Learning Engineer TS/SCI
Status: Full-Time
Location: Huntsville, Alabama

Position Overview

A growing defense-focused organization is seeking an experienced Machine Learning Engineer to support advanced intelligence and analytics initiatives in Huntsville, Alabama. This is an onsite role supporting mission-critical projects involving large-scale data processing, machine learning model deployment, and system integration.
This role is ideal for someone who thrives in highly secure environments and has experience taking machine learning solutions from concept through production deployment.

Key Responsibilities
  • Design and integrate machine learning systems with broader software platforms and infrastructure
  • Build and optimize data pipelines that support machine learning workflows
  • Transition machine learning prototypes into production-ready solutions
  • Develop deployment pipelines for machine learning models
  • Monitor model performance and address model drift, failures, and rollback scenarios
  • Conduct testing, experimentation, and documentation of model performance
  • Write clean, scalable, and maintainable code primarily in Python
  • Collaborate with technical teams to ensure machine learning solutions align with overall architecture
  • Support CI/CD workflows and GitOps practices
Technology Environment
  • Python
  • Docker
  • Jupyter Notebooks
  • PostgreSQL
  • GitLab
  • GitHub
  • SQL/NoSQL databases
  • Linux and Windows environments
Required Qualifications
  • Bachelor's degree in Computer Science, Statistics, Mathematics, Physics, or another quantitative discipline
  • Minimum of 12 years of overall professional experience
  • 1-3 years of hands-on experience working with machine learning frameworks
  • Strong programming experience in Python
  • Deep understanding of machine learning frameworks, libraries, data structures, and data modeling
  • Experience with SQL and NoSQL databases
  • Knowledge of CI/CD pipelines and Agile development methodologies
  • Understanding of software design principles and system integration
  • Active TS/SCI clearance with ability to obtain a CI Polygraph after onboarding
Preferred Qualifications
  • Master's degree in a related field with 12 years of experience
    OR
  • Bachelor's degree in a related field with 17 years of experience
  • Experience working with petabyte-scale datasets
  • Background in multi-source intelligence analytics
  • Experience deploying, monitoring, and scaling machine learning models in production environments
Key Skills Required
  • Machine Learning Model Deployment
  • Python Development
  • Data Pipeline Engineering
  • CI/CD Implementation
  • Cloud/Container Technologies
  • System Integration
  • Database Management

Apply