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Senior Meta Machine Learning Jobs in Suwanee, GA

Five and Fly

Machine Learning Engineer

Atlanta, GA · On-site

Machine Learning Engineer Employment Type: Full Time Location: Atlanta, GA Description We are ... Meta LLaMA (fine-tuned/custom models for domain-specific tasks). * Collaborate with Data ...

Speria

Machine Learning Engineer

Atlanta, GA · On-site

$120 - $160/hr

... work with senior and executive management. Job Summary We are seeking a highly skilled and ... Design and build machine learning and optimization pipelines * Develop and deploy production-grade ...

Warnerbros

Senior Machine Learning Engineer

Atlanta, GA · On-site

$100K - $138K/yr

Senior Machine Learning Engineer Team: Data & Audience Platform (DAP) - ML Engineering What We Do Warner Bros. Discovery (WBD) is home to the world's most iconic entertainment, news, and sports ...

Workday

Sr Machine Learning Engineer

Atlanta, GA

$159K - $276K/yr

Proven understanding of machine learning algorithms (supervised, unsupervised) and model evaluation techniques. Ability to define and track and identify key product metrics. Excellent communication ...

FanDuel

Senior Machine Learning Engineer

Atlanta, GA · On-site

$100K - $138K/yr

We are looking for Senior Machine Learning Engineer who may be looking to make the move to a big data environment. If this describes you, read on - we want to hear from you! THE GAME PLAN Everyone on ...

FanDuel

Senior Machine Learning Engineer

Atlanta, GA · On-site

$100K - $138K/yr

We are looking for Senior Machine Learning Engineer who may be looking to make the move to a big data environment. If this describes you, read on - we want to hear from you! THE GAME PLAN Everyone on ...

FanDuel

Senior Machine Learning Engineer

Atlanta, GA · On-site

$100K - $138K/yr

We are looking for Senior Machine Learning Engineer who may be looking to make the move to a big data environment. If this describes you, read on - we want to hear from you! THE GAME PLAN Everyone on ...

Patientco

Senior Machine Learning Engineer I

Atlanta, GA

$117K - $155K/yr

ABOUT THIS POSITION We are seeking a highly skilled and innovative Senior ML Engineer with a ... Deep understanding of machine learning fundamentals, including supervised, unsupervised, and ...

Waystar

Senior Machine Learning Engineer I

Atlanta, GA · On-site

$117K - $155K/yr

ABOUT THIS POSITION We are seeking a highly skilled and innovative Senior ML Engineer with a ... Deep understanding of machine learning fundamentals, including supervised, unsupervised, and ...

Speria

Machine Learning Operations Engineer

Atlanta, GA · On-site

$120 - $180/hr

... work with senior and executive management. Job Summary We are seeking a highly skilled and ... The MLOps Engineer works closely with Machine Learning Engineers and Data Engineers to ensure that ...

SAP SuccessFactors

Machine Learning Expert

Atlanta, GA · On-site

$152K - $254K/yr

Machine Learning Expert Location: Atlanta, GA Work Model: Hybrid Work Model. Purpose and Objective ... Mentor and guide engineers from junior to senior levels, fostering technical excellence. Partner ...

SAP

Machine Learning Expert

Atlanta, GA · On-site

$152K - $254K/yr

Machine Learning Expert Location: Atlanta, GA Work Model: Hybrid Work Model. Purpose and Objective ... Mentor and guide engineers from junior to senior levels, fostering technical excellence. Partner ...

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All JobsMeta Machine Learning JobsSenior Meta Machine Learning JobsSenior Meta Machine Learning Jobs in Suwanee, GA

Senior Meta Machine Learning information

See Suwanee, GA salary details

$23.3K

$74.7K

$152.2K

How much do senior meta machine learning jobs pay per year?

As of Sep 5, 2026, the average yearly pay for senior meta machine learning in Suwanee, GA is $74,728.00, according to ZipRecruiter salary data. Most workers in this role earn between $38,600.00 and $95,900.00 per year, depending on experience, location, and employer.

What is the difference between Senior Meta Machine Learning vs Data Scientist?

AspectSenior Meta Machine LearningData Scientist
Required CredentialsMaster's or PhD in CS, ML, or related fields; experience with meta-learning frameworksBachelor's or higher in CS, Statistics, or related fields; proficiency in data analysis
Work EnvironmentResearch-focused teams developing advanced ML models, often in AI companiesData analysis, modeling, and visualization across various industries
Employer & Industry UsageTech firms, AI startups, research institutionsFinance, healthcare, e-commerce, tech companies

While both roles involve machine learning expertise, Senior Meta Machine Learning specialists focus on developing advanced meta-learning algorithms, often in research settings, whereas Data Scientists apply data analysis and modeling techniques across diverse industries. The roles share similar educational backgrounds but differ in focus and application.

What job categories do people searching Senior Meta Machine Learning jobs in Suwanee, GA look for?

The top searched job categories for Senior Meta Machine Learning jobs in Suwanee, GA are:

What cities near Suwanee, GA are hiring for Senior Meta Machine Learning jobs?

Cities near Suwanee, GA with the most Senior Meta Machine Learning job openings:

Senior Meta Machine Learning jobs near you
Infographic showing various Senior Meta Machine Learning job openings in Suwanee, GA as of August 2026, with employment types broken down into 1% As Needed, 71% Full Time, 26% Part Time, and 2% Contract. Highlights an 83% Physical, 2% Hybrid, and 15% Remote job distribution, with an average salary of $74,728 per year, or $35.9 per hour.

Machine Learning Engineer

Five and Fly

Atlanta, GA • On-site

Full-time

Re-posted 15 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.

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