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Participate Learning Jobs in Atlanta, GA (NOW HIRING)

Five and Fly

Machine Learning Engineer

Atlanta, GA · On-site

Machine Learning Engineer Employment Type: Full Time Location: Atlanta, GA Description We are ... Participate in design reviews, architecture discussions, and model evaluations. * Document ...

Tihinsurance

Machine Learning Engineer

Alpharetta, GA · On-site

... learning function at a market-leading insurance company. As one of the first data science hires ... Actively participate in refining user stories. Responsible for design, developing, and maintaining ...

Autodesk

Senior Machine Learning Test Engineer

Atlanta, GA · On-site +1

$106K - $138K/yr

Participate in code reviews and provide constructive feedback to peers * Document and present ... Passion for learning new technologies and improving existing systems * Experience with cloud ...

Chroma Early Learning Academy

Lead Teacher

Atlanta, GA · On-site

$13 - $15/hr

Collaborate with other teachers and staff to create a cohesive learning experience. Participate in regular professional development and team meetings. Ensure compliance with state licensing ...

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Showing results 21-40

All JobsParticipate Learning JobsParticipate Learning Jobs in Atlanta, GA

Participate Learning information

See Atlanta, GA salary details

$10.6K

$80.7K

$134.6K

How much do participate learning jobs pay per year?

As of Aug 8, 2026, the average yearly pay for participate learning in Atlanta, GA is $80,668.00, according to ZipRecruiter salary data. Most workers in this role earn between $69,200.00 and $133,700.00 per year, depending on experience, location, and employer.

What are the main responsibilities and collaborative aspects of working as a teacher with Participate Learning's global education programs?

As a teacher with Participate Learning, you will typically be responsible for delivering curriculum content while incorporating global perspectives and cultural exchange in the classroom. The role involves close collaboration with local teaching staff, school administrators, and fellow international educators to enrich students’ learning experiences. Teachers are also expected to contribute to school community activities and professional development sessions, fostering a supportive environment for both students and colleagues. This collaborative and multicultural setting offers opportunities to develop new teaching strategies, gain international experience, and advance your career in global education.

What are the key skills and qualifications needed to thrive as a teacher with Participate Learning, and why are they important?

To thrive as a teacher with Participate Learning, you need a teaching degree, state certification, and a strong understanding of curriculum development and classroom management. Familiarity with digital learning platforms, educational technology, and assessment tools is typically required. Cultural adaptability, strong communication, and collaboration skills help teachers engage diverse student populations and work effectively in international settings. These abilities are crucial for fostering a positive learning environment and achieving educational outcomes in globally-minded classrooms.

What is Participate Learning?

Participate Learning is an educational organization that partners with schools and districts to provide global education programs, including international teacher exchange, dual language immersion, and global leadership development. Their primary focus is to bring experienced international educators into U.S. classrooms to promote cultural exchange and global awareness among students. Participate Learning supports teachers through professional development, resources, and a supportive community, aiming to enrich education by fostering cross-cultural understanding.

What is the difference between Participate Learning vs ESL Teacher?

AspectParticipate LearningESL Teacher
CredentialsTeaching certification, TESOL/TEFLTeaching certification, TESOL/TEFL
Work EnvironmentInternational schools, cultural exchange programsLanguage schools, public/private schools, online platforms
Industry UsageGlobal education programs, cultural immersionLanguage instruction, ESL programs

Participate Learning and ESL Teachers both require teaching certifications and often work in educational settings focused on language and cultural exchange. While Participate Learning emphasizes international programs and cultural immersion, ESL Teachers primarily focus on language instruction within local or online classrooms. Both roles serve the education industry but differ in scope and environment.

What are popular job titles related to Participate Learning jobs in Atlanta, GA? For Participate Learning jobs in Atlanta, GA, the most frequently searched job titles are:
What job categories do people searching Participate Learning jobs in Atlanta, GA look for? The top searched job categories for Participate Learning jobs in Atlanta, GA are:
What cities near Atlanta, GA are hiring for Participate Learning jobs? Cities near Atlanta, GA with the most Participate Learning job openings:
Participate Learning jobs near you
Infographic showing various Participate Learning job openings in Atlanta, GA as of August 2026, with employment types broken down into 50% Full Time, and 50% Part Time. Highlights an 100% In-person job distribution, with an average salary of $80,668 per year, or $38.8 per hour.

Machine Learning Engineer

Five and Fly

Atlanta, GA • On-site

Full-time

Re-posted 17 days ago

Job description

Machine Learning Engineer
Department: Machine Learning Engineer
Employment Type: Full Time
Location: Atlanta, GA
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.
Key Responsibilities
  • 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).
  • 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.
  • 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.
  • 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.

Skills, Knowledge and Expertise
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.
  • 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.

Seeking following AFSC/MOSs
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 Operator26XX Intel (with data/automation focus)
US Space Force:Cyber Operations (DCO/OCO) Guardians

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