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Apprentice Machine Learning Testing Jobs in Florida

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... testing frameworks. Highly Advantageous Capabilities * Exposure to foundational radio-frequency machine learning (RFML) or traditional digital signal processing. * Familiarity training Large Language ...

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Be Seen First

... testing frameworks. Highly Advantageous Capabilities * Exposure to foundational radio-frequency machine learning (RFML) or traditional digital signal processing. * Familiarity training Large Language ...

New

Machine learning algorithms, including natural language processing (NLP) techniques; * Foundation in statistical methods such as hypothesis testing, confidence intervals, and regression analysis;

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

In this role, you will participate in tasks that help improve machine learning models, including data labeling, content evaluation, and user-based testing. Projects may vary in scope and format ...

... data for machine learning pipelines, feature engineering, and model lifecycle management ... testing, and secure deployment - Ensures solutions comply with DoD cybersecurity, RMF, data ...

New

... data for machine learning pipelines, feature engineering, and model lifecycle management ... testing, and secure deployment - Ensures solutions comply with DoD cybersecurity, RMF, data ...

New

... data for machine learning pipelines, feature engineering, and model lifecycle management ... testing, and secure deployment - Ensures solutions comply with DoD cybersecurity, RMF, data ...

New

... data for machine learning pipelines, feature engineering, and model lifecycle management ... testing, and secure deployment - Ensures solutions comply with DoD cybersecurity, RMF, data ...

New

... data for machine learning pipelines, feature engineering, and model lifecycle management ... testing, and secure deployment - Ensures solutions comply with DoD cybersecurity, RMF, data ...

New

... data for machine learning pipelines, feature engineering, and model lifecycle management ... testing, and secure deployment - Ensures solutions comply with DoD cybersecurity, RMF, data ...

New

... data for machine learning pipelines, feature engineering, and model lifecycle management ... testing, and secure deployment - Ensures solutions comply with DoD cybersecurity, RMF, data ...

New

... data for machine learning pipelines, feature engineering, and model lifecycle management ... testing, and secure deployment - Ensures solutions comply with DoD cybersecurity, RMF, data ...

New

... data for machine learning pipelines, feature engineering, and model lifecycle management ... testing, and secure deployment - Ensures solutions comply with DoD cybersecurity, RMF, data ...

New

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Apprentice Machine Learning Testing information

What are the key skills and qualifications needed to thrive as an Apprentice Machine Learning Testing, and why are they important?

To thrive as an Apprentice in Machine Learning Testing, a foundational understanding of statistics, programming (especially Python), and basic machine learning concepts is essential, often supported by a degree or coursework in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, Jupyter Notebooks, and version control systems is typically required. Strong analytical thinking, attention to detail, and effective communication skills help apprentices collaborate and identify testing issues efficiently. These skills ensure accurate model validation, effective troubleshooting, and contribute to the robust deployment of machine learning solutions.

What kinds of projects or tasks can I expect to work on as an Apprentice Machine Learning Testing?

As an Apprentice Machine Learning Testing, you’ll typically assist in evaluating machine learning models by designing and running tests, analyzing model outputs, and helping identify issues like bias or overfitting. You may work closely with data scientists and software engineers to validate model performance and ensure results align with project objectives. Your daily tasks might include preparing test datasets, executing automated testing scripts, and documenting findings to help improve model reliability. This role often serves as a valuable introduction to practical machine learning workflows and quality assurance processes in technical teams.

What does an Apprentice Machine Learning Testing do?

An Apprentice Machine Learning Testing professional assists in evaluating and validating machine learning models to ensure they perform as expected. They typically work under the guidance of experienced data scientists or engineers, running tests, analyzing results, and helping to identify issues such as bias or inaccuracies in algorithms. Their responsibilities may also include developing test cases, writing reports, and learning about data preprocessing and evaluation metrics. This role is ideal for those who are new to the field and want to build foundational skills in machine learning quality assurance.

What is the difference between Apprentice Machine Learning Testing vs Machine Learning Engineer?

AspectApprentice Machine Learning TestingMachine Learning Engineer
Required CredentialsBasic understanding of ML concepts, often pursuing relevant certifications or degreesAdvanced degrees (BSc, MSc, PhD) in CS or related fields, with extensive experience
Work EnvironmentEntry-level, supervised testing environments, often in training programsFull-time, independent development and deployment of ML models in production
Employer & Industry UsageInternships, training programs, entry-level roles in tech companiesEstablished tech firms, startups, research institutions

Apprentice Machine Learning Testing roles focus on learning and assisting with testing ML models under supervision, while Machine Learning Engineers design, build, and deploy ML systems independently. The apprentice position is ideal for gaining foundational skills, whereas the engineer role requires advanced expertise and experience.

What are popular job titles related to Apprentice Machine Learning Testing jobs in Florida? For Apprentice Machine Learning Testing jobs in Florida, the most frequently searched job titles are:
What job categories do people searching Apprentice Machine Learning Testing jobs in Florida look for? The top searched job categories for Apprentice Machine Learning Testing jobs in Florida are:
What cities in Florida are hiring for Apprentice Machine Learning Testing jobs? Cities in Florida with the most Apprentice Machine Learning Testing job openings:
AI/ML Software Engineer - TS/SCI

AI/ML Software Engineer - TS/SCI

StaffRight Associates - Recruitment & Staffing

Sarasota, FL • On-site

$135K - $180K/yr

Full-time

Medical, Dental, Vision, Retirement, PTO

This job post has expired 1 day ago. Applications are no longer accepted.


Job description

Active TS/SCI Security Clearance and valid United States citizenship (mandatory for consideration).


The Opportunity

StaffRight Associates has partnered with an elite defense innovator to secure a high-caliber AI/ML Software Engineer capable of transforming complex signal intelligence data into actionable, automated insights. In this critical role, you will architect and deploy cutting-edge intelligent systems that support high-stakes Department of Defense and Intelligence Community missions. This is a rare opportunity to directly impact national security by building adaptive, self-governing analytical models that operate in highly dynamic, real-time environments.


What You’ll Do

  • Architect and implement advanced artificial intelligence and machine learning architectures optimized for sophisticated intelligence parsing and tactical choice-generation.
  • Engine predictive models using continuous data streams to execute anomaly detection, recognize intricate operational patterns, and classify complex, time-dependent events.
  • Integrate intelligent analytical pipelines seamlessly into large-scale enterprise frameworks, balancing high-speed execution with rigorous security protocols and long-term system stability.
  • Synthesize self-governing computational tools capable of processing raw data streams to extract key hidden characteristics and infer operational states with minimal user oversight.
  • Collaborate with cross-functional technical leaders to design comprehensive sensor processing networks that provide clear, intelligent clarity to frontline decision-makers.


What You Bring - Absolute Requirements

  • Active TS/SCI Security Clearance and valid United States citizenship (mandatory for consideration).
  • Academic Pedigree: Bachelor of Science degree or higher in Computer Science, Electrical Engineering, Aerospace Engineering, Applied Mathematics, or a highly technical equivalent field.
  • Professional Experience: A minimum of 1 year of professional, hands-on exposure building machine learning infrastructure (3 to 5 years of established pedigree preferred).
  • Technical Mastery: Deep familiarity with model training lifecycle execution and industry-standard machine learning frame-ecosystems (such as PyTorch, TensorFlow, or scikit-learn).
  • Engineering Foundation: Strong programming proficiency alongside direct application of mathematical and signal-processing analytical toolsets.
  • Architecture Familiarity: Proven understanding of advanced deep learning mechanics, neural networks, transformer frameworks, and attention-based mechanisms.
  • Operational Discipline: Comprehensive knowledge of MLOps methodologies, automated data ingestion pipelines, and rigorous validation/testing frameworks.


Highly Advantageous Capabilities

  • Exposure to foundational radio-frequency machine learning (RFML) or traditional digital signal processing.
  • Familiarity training Large Language Models, refining prompt structures, or building advanced multi-modal agent frameworks utilizing RAG, Chain-of-Thought, or multi-agent reinforcement learning.
  • Hands-on proficiency containerizing applications utilizing Docker or Kubernetes, alongside deployment experience across cloud platforms like AWS Bedrock, Azure OpenAI, or Google Vertex AI.
  • Mastery of low-latency model serving, real-time inference optimization, A/B testing, and continuous model performance telemetry.
  • Insight into adversarial AI defense, graph neural networks for network topology analysis, or an established track record of shipping end-to-end ML applications to production.


Company Description

Joining StaffRight Associates
When you partner with StaffRight Associates in your search for your next role, you’re doing more than pursuing a job, you’re aligning yourself with a team of experts committed to placing top-tier talent in truly impactful positions.
We take pride in fostering professional growth and connecting forward-thinking individuals with organizations that value innovation and excellence. We look forward to showcasing your expertise in a way that resonates with our clients and opens the door to meaningful opportunities.