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Assistant Learning Specialist Jobs in Decatur, GA

Staff Financial Group

AR Specialist

Smyrna, GA · Hybrid

$50K - $65K/yr

... Assist in credit evaluation and setting credit limits ● Collaborate with internal teams to ... you're interested in learning more about this opportunity or would like to discuss your ...

nLeague

HCM Training Specialist

Atlanta, GA · On-site

We are looking for a dynamic, data-driven, and detail-oriented contributor to assist in providing ... Assisting with maintenance of HRA's Learning Management System (LMS), to include responding to ...

HANSGROHE

Product Engineering Specialist

Alpharetta, GA · On-site

$71K - $90K/yr

S. production operations. * Assist with setup and management of Manufacture/custom products and ... Professional Development & Technical Learning * Develop working knowledge of manufacturing ...

Trilyon, Inc.

HCM Training Specialist

Atlanta, GA · On-site

Human Capital Management (HCM) Training Specialist Location: Atlanta, GA 30334, (Hybrid) Duration ... Utilize systems training environments and tools for student activities. * Assist with Learning ...

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Assistant Learning Specialist information

What qualifications do you need for an LSA?

An Assistant Learning Specialist typically needs a bachelor's degree in education, psychology, or a related field. Relevant experience working with students, strong communication skills, and knowledge of educational strategies are also important; some positions may require certification or training in special education or related areas.

What does a learning specialist do?

A learning specialist helps students improve their academic skills by assessing learning needs, developing personalized strategies, and providing targeted instruction. They often work in educational settings, using tools like assessments and learning plans, and may hold certifications in special education or related fields.

What are the key skills and qualifications needed to thrive as an Assistant Learning Specialist, and why are they important?

To thrive as an Assistant Learning Specialist, you need a solid understanding of educational theory, instructional strategies, and typically a bachelor’s degree in education or a related field. Familiarity with learning management systems (LMS), educational technology tools, and assessment software is often required. Strong communication, patience, and collaboration skills help build rapport with students and support the lead specialist effectively. These skills and qualities are essential for creating supportive learning environments and facilitating student success.

What degree do you need to be a learning specialist?

To become a learning specialist, a bachelor's degree in education, psychology, special education, or a related field is typically required. Many employers prefer candidates with a master's degree and relevant certifications, such as a teaching license or special education credential, along with experience working with diverse learners.

How does an Assistant Learning Specialist typically collaborate with teachers and other educational staff?

Assistant Learning Specialists frequently work alongside classroom teachers, special education professionals, and counselors to create and implement individualized learning plans for students. They support teachers by adapting instructional materials, monitoring student progress, and providing one-on-one or small group assistance. Regular communication and teamwork are essential, as Assistant Learning Specialists help ensure that students with diverse learning needs receive appropriate support and accommodations.

What does an Assistant Learning Specialist do?

An Assistant Learning Specialist supports students and educators by helping to develop, implement, and monitor learning strategies that improve academic performance. They often work alongside lead learning specialists to assess students' strengths and challenges, create individualized learning plans, and provide direct academic support. Additionally, they may collaborate with teachers and parents to ensure that students receive the necessary accommodations and interventions. Their role is vital in fostering an inclusive learning environment where all students can succeed.

What jobs pay 4000 a week without a degree?

An Assistant Learning Specialist typically requires relevant experience and specialized skills rather than a high weekly income without a degree. High-paying roles that can reach $4,000 a week without a degree often include sales, real estate, certain trades like plumbing or electrical work, and entrepreneurial ventures. These jobs usually depend on performance, certifications, or self-employment rather than formal education alone.
Assistant Learning Specialist jobs near you

Machine Learning Engineer

Five and Fly, LLC.

Atlanta, GA

Full-time

Posted yesterday

Job description

We are seeking a skilled and forward-looking ML Engineer with experience in Large Language Models (LLMs), generative AI, and agentic architectures to join our growing R&D and Applied AI team. This role is critical in helping Oversight deliver the next generation of agentic AI systems for enterprise spend management and risk controls.
 
The ideal candidate has a strong foundation in machine learning, modern deep learning frameworks, and data pipelines, coupled with hands-on experience experimenting with LLMs, small language models (SLMs), multi-agent frameworks, and retrieval-augmented generation (RAG).

You will work closely with AI/ML researchers, data engineers, and product teams to design, implement, and optimize models that power autonomous exception resolution, anomaly detection, and explainable insights. This is a hands-on engineering role where you will not only build and scale ML systems but also actively contribute to cutting-edge applied research in agentic AI.
Core ML/LLM Engineering
  • Contribute to the design, training, fine-tuning, and deployment of ML/LLM models for production.
  • Implement RAG pipelines using vector databases.
  • Work with frameworks like LangChain, LangGraph, MCP to prototype and optimize multi-agent workflows.
  • Develop prompt engineering, optimization, and safety techniques for agentic LLM interactions.
  • Integrate memory, evidence packs, and explainability modules into agentic pipelines.
  • Work hands-on with multiple LLM ecosystems:
    • OpenAI GPT models (GPT-4, GPT-4o, fine-tuned GPTs).
    • Anthropic Claude (Claude 2/3 for reasoning and safety-aligned workflows).
    • Google Gemini (multimodal reasoning, advanced RAG integration).
    • Meta LLaMA (fine-tuned/custom models for domain-specific tasks).
Data & Infrastructure
  • Collaborate with Data Engineering to build and maintain real-time and batch data pipelines that serve ML/LLM workloads.
  • Conduct feature engineering, preprocessing, and embeddings generation for structured and unstructured data.
  • Implement model monitoring, drift detection, and retraining pipelines.
  • Leverage cloud ML platforms (AWS Sagemaker, Databricks ML) for experimentation and scaling.
Research & Applied Innovation
  • Explore and evaluate emerging LLM/SLM architectures and agent orchestration patterns.
  • Experiment with generative AI and multimodal models to extend capabilities beyond text (images, structured financial data).
  • Collaborate with R&D to prototype autonomous resolution agents, anomaly detection models, and reasoning engines.
  • Translate research prototypes into production-ready components.
Collaboration & Delivery
  • Work cross-functionally with R&D, Data Science, Product, and Engineering to deliver business-aligned AI features.
  • Participate in design reviews, architecture discussions, and model evaluations.
  • Document processes, experiments, and results effectively for knowledge sharing.
  • Mentor junior engineers and contribute to ML engineering best practices.
Required
  • Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or related field.
  • 3+ years of experience building and deploying ML systems.
  • Proficiency in Python and libraries such as PyTorch, TensorFlow, Scikit-Learn, Hugging Face Transformers.
  • Hands-on experience with LLMs/SLMs (fine-tuning, prompt design, inference optimization).
  • Demonstrated experience with at least two of the following ecosystems:
    1. OpenAI GPT models (chat, assistants, fine-tuning).
    2. Anthropic Claude (safety-first AI for reasoning and summarization).
    3. Google Gemini (multimodal reasoning, enterprise-scale APIs).
    4. Meta LLaMA (open-source, fine-tuned models).
  • Familiarity with vector databases, embeddings, and RAG pipelines.
  • Ability to work with structured and unstructured data at scale.
  • Knowledge of SQL and distributed data frameworks (Spark, Ray).
  • Strong understanding of ML lifecycle: data prep, training, evaluation, deployment, monitoring.
Preferred Qualifications
  • Experience with agentic frameworks (LangChain, LangGraph, MCP, AutoGen).
  • Knowledge of AI safety, guardrails, and explainability techniques.
  • Hands-on experience deploying ML/LLM solutions in cloud environments (AWS, GCP, Azure).
  • Experience with CI/CD for ML (MLOps), monitoring, and observability.
  • Familiarity with anomaly detection, fraud/risk modeling, or behavioral analytics.
  • Contributions to open-source AI/ML projects or publications in applied ML research.
US Army:
17D - Cyber Capability Developer
17C - Cyber Operations Specialist (Advanced Track)
35Q - Cryptologic Network Warfare Specialist
35N / 35P / 35S (Intel Analysts w/ coding exposure)
US AirForce:
17X - Cyberspace Warfare Operations
1B4X1 - Cyber Warfare Operations
9S100 - Scientific Applications Specialist
3D0X4 / 1D7X1 (Software / Data Ops variants)

US Navy:
CTN - Cryptologic Technician (Networks)
CTI / CTR (with analytics focus)
Information Warfare Officers (1810)
US Marine Corps:
1721 - Cyberspace Warfare Operator
26XX Intel (with data/automation focus)
US Space Force:
Cyber Operations (DCO/OCO) Guardians

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