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Contract Meta Machine Learning Jobs in Georgia (NOW HIRING)

What We Look For In a Machine Learning Tutor * Advanced Subject Mastery: Deep knowledge of ... Varsity Tutors does not contract in: Alaska, California, Colorado, Delaware, Hawaii, Maine, New ...

What We Look For In a Machine Learning Tutor * Advanced Subject Mastery: Deep knowledge of ... Varsity Tutors does not contract in: Alaska, California, Colorado, Delaware, Hawaii, Maine, New ...

What We Look For In a Machine Learning Tutor * Advanced Subject Mastery: Deep knowledge of ... Varsity Tutors does not contract in: Alaska, California, Colorado, Delaware, Hawaii, Maine, New ...

What We Look For In a Machine Learning Tutor * Advanced Subject Mastery: Deep knowledge of ... Varsity Tutors does not contract in: Alaska, California, Colorado, Delaware, Hawaii, Maine, New ...

What We Look For In a Machine Learning Tutor * Advanced Subject Mastery: Deep knowledge of ... Varsity Tutors does not contract in: Alaska, California, Colorado, Delaware, Hawaii, Maine, New ...

What We Look For In a Machine Learning Tutor * Advanced Subject Mastery: Deep knowledge of ... Varsity Tutors does not contract in: Alaska, California, Colorado, Delaware, Hawaii, Maine, New ...

What We Look For In a Machine Learning Tutor * Advanced Subject Mastery: Deep knowledge of ... Varsity Tutors does not contract in: Alaska, California, Colorado, Delaware, Hawaii, Maine, New ...

What We Look For In a Machine Learning Tutor * Advanced Subject Mastery: Deep knowledge of ... Varsity Tutors does not contract in: Alaska, California, Colorado, Delaware, Hawaii, Maine, New ...

What We Look For In a Machine Learning Tutor * Advanced Subject Mastery: Deep knowledge of ... Varsity Tutors does not contract in: Alaska, California, Colorado, Delaware, Hawaii, Maine, New ...

What We Look For In a Machine Learning Tutor * Advanced Subject Mastery: Deep knowledge of ... Varsity Tutors does not contract in: Alaska, California, Colorado, Delaware, Hawaii, Maine, New ...

What We Look For In a Machine Learning Tutor * Advanced Subject Mastery: Deep knowledge of ... Varsity Tutors does not contract in: Alaska, California, Colorado, Delaware, Hawaii, Maine, New ...

What We Look For In a Machine Learning Tutor * Advanced Subject Mastery: Deep knowledge of ... Varsity Tutors does not contract in: Alaska, California, Colorado, Delaware, Hawaii, Maine, New ...

GA

$88K/yr

Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment. Meta is committed to providing reasonable accommodations ...

GA

$104K/yr

Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment. Meta is committed to providing reasonable accommodations ...

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Contract Meta Machine Learning information

What are the key skills and qualifications needed to thrive as a Contract Meta Machine Learning Engineer, and why are they important?

To thrive as a Contract Meta Machine Learning Engineer, you need a strong background in computer science, statistics, and advanced machine learning concepts, often supported by a relevant degree or equivalent experience. Familiarity with programming languages like Python, frameworks such as TensorFlow or PyTorch, and version control systems is essential, along with experience in meta-learning techniques. Strong analytical thinking, problem-solving abilities, and effective communication skills help you design innovative solutions and collaborate with diverse teams. These competencies are crucial to efficiently develop, implement, and optimize meta-learning models that address complex, evolving business challenges.

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

AspectContract Meta Machine LearningContract Data Scientist
Required CredentialsMaster's or PhD in Computer Science, Data Science, or related fields; experience with machine learning frameworksMaster's or PhD in Data Science, Statistics, or related fields; strong programming skills
Work EnvironmentFocus on developing and deploying machine learning models, often in AI projectsData analysis, modeling, and interpretation to inform business decisions
Employer & Industry UsageTech companies, AI startups, research institutionsFinance, healthcare, marketing, and tech firms

Contract Meta Machine Learning roles primarily focus on building and deploying machine learning models, often requiring advanced technical skills in AI. Contract Data Scientist positions involve analyzing data, creating models, and deriving insights for business strategies. While both roles require strong analytical skills and similar educational backgrounds, Meta Machine Learning roles are more specialized in AI development, whereas Data Scientist roles emphasize data analysis and interpretation.

What are some of the unique challenges faced by contract machine learning engineers at Meta, and how can candidates prepare for them?

Contract machine learning engineers at Meta often work on high-impact projects with tight deadlines and rapidly evolving requirements. One of the main challenges is quickly integrating into existing teams and understanding Meta's large-scale data infrastructure and proprietary tools. To prepare, candidates should familiarize themselves with Meta's open-source frameworks, practice adapting to new codebases, and be ready to communicate effectively with cross-functional stakeholders. Building strong collaboration skills and maintaining flexibility will help contract engineers deliver value efficiently in this fast-paced environment.

What are Contract Meta Machine Learning professionals?

Contract Meta Machine Learning professionals are specialists hired on a contractual basis to design, develop, and optimize machine learning models, often focusing on meta-learning techniques. Meta-learning, sometimes called 'learning to learn,' involves creating algorithms that can adapt to new tasks with minimal data or retraining. These professionals typically work with organizations to solve complex, data-driven problems, leveraging advanced AI techniques for efficiency and scalability. They may also help integrate these solutions into existing systems and provide guidance on best practices for model deployment.
What are the most commonly searched types of Meta Machine Learning jobs in Georgia? The most popular types of Meta Machine Learning jobs in Georgia are:
What are popular job titles related to Contract Meta Machine Learning jobs in Georgia? For Contract Meta Machine Learning jobs in Georgia, the most frequently searched job titles are:
What job categories do people searching Contract Meta Machine Learning jobs in Georgia look for? The top searched job categories for Contract Meta Machine Learning jobs in Georgia are:
What cities in Georgia are hiring for Contract Meta Machine Learning jobs? Cities in Georgia with the most Contract Meta Machine Learning job openings:
Infographic showing various Contract Meta Machine Learning job openings in Georgia as of June 2026, with employment types broken down into 62% Full Time, 13% Part Time, and 25% Contract. Highlights an 62% In-person, and 38% Remote job distribution.

Full-time

Posted 26 days ago


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.
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