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Python Ml Developer Jobs in Marietta, GA (NOW HIRING)

Worldpay

ML Software Engineering Lead

Atlanta, GA · On-site

$98K - $129K/yr

Worldpay is seeking an experienced and visionary ML Software Engineering Lead to serve as the ... DevOps best practices. • Strong Python skills, including in relevant libraries such as Pandas ...

Sumeru

Senior AI/ML Engineer

Atlanta, GA · On-site

$100K - $138K/yr

Senior AI/ML Engineer Location: Bellevue/Seattle, WA ; Atlanta, GA, and Frisco, TX Need Local ... Python (required) * Libraries: scikit-learn, HuggingFace Transformers, RapidFuzz, jellyfish

Worldpay

ML Software Engineering Lead

Atlanta, GA

$98K - $129K/yr

We are seeking an experienced and visionary ML Software Engineering Lead to serve as the technical ... DevOps best practices. * Strong Python skills, including in relevant libraries such as Pandas ...

Intellectt INC

Agentic AI Engineer (Python)

Atlanta, GA · On-site

Strong programming skills in Python and familiarity with AI/ML frameworks. * Proven experience developing LLM-driven or multi-agent AI systems. * Hands-on experience with LangChain, AutoGen, CrewAI ...

Worldpay

Senior ML Software Engineer

Atlanta, GA

$117K - $155K/yr

Strong Python programming and relevant ML/data libraries * Experience with containerization, orchestration, and AWS cloud services * Building and operating CI/CD pipelines * Monitoring ...

WorkNovas LLC

AI/ML Quality Engineer

Atlanta, GA · On-site

$69K - $89K/yr

Strong proficiency in Python (FastAPI, Flask, async programming, RESTful APIs). * Proven experience in AI/ML pipelines - data preprocessing, model training, fine-tuning, and deployment (TensorFlow ...

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All JobsPython Ml Developer JobsPython Ml Developer Jobs in Marietta, GA

Python Ml Developer information

See Marietta, GA salary details

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How much do python ml developer jobs pay per hour?

As of Jul 14, 2026, the average hourly pay for python ml developer in Marietta, GA is $55.57, according to ZipRecruiter salary data. Most workers in this role earn between $45.82 and $63.12 per hour, depending on experience, location, and employer.

What does a Python ML Developer do?

A Python ML Developer designs, builds, and deploys machine learning models using the Python programming language. They work with large datasets, clean and process data, select appropriate algorithms, and use libraries like TensorFlow, PyTorch, or scikit-learn to implement solutions. Their work often involves collaborating with data scientists and engineers to integrate machine learning models into applications. Additionally, they may be responsible for testing, tuning, and optimizing models to achieve the best possible performance in real-world scenarios.

What are some common challenges Python ML Developers face when deploying machine learning models to production?

Python ML Developers often encounter challenges such as ensuring model scalability, managing dependencies, and maintaining reproducibility when deploying models into production environments. Integrating machine learning models with existing systems can require close collaboration with DevOps and software engineering teams to streamline workflows and automate deployment pipelines. Additionally, monitoring model performance over time and handling data drift are crucial responsibilities to ensure continued accuracy and reliability of deployed solutions.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and maintain AI and machine learning systems. While AI automation tools can handle certain tasks, MLEs are essential for creating, optimizing, and interpreting complex models, making complete replacement unlikely in the near term. MLEs need skills in programming, data analysis, and model deployment to adapt to evolving AI technologies.

What is a $900000 AI job?

A $900,000 AI job typically refers to a high-paying position in artificial intelligence, such as senior machine learning engineer or AI research director, often requiring advanced skills in deep learning, data science, and programming with tools like Python and TensorFlow. Such roles usually involve leadership, strategic planning, and extensive experience in the field.

Which 3 jobs will survive AI?

For a Python ML Developer, roles that require complex problem-solving, creativity, and human judgment are likely to persist, such as AI research scientist, data scientist, and software engineer. These jobs involve designing, interpreting, and improving AI models, which currently require advanced expertise, critical thinking, and domain knowledge that AI cannot fully replicate. Continuous learning and staying updated with new tools and techniques are essential for long-term career resilience.

What are the key skills and qualifications needed to thrive as a Python ML Developer, and why are they important?

To thrive as a Python ML Developer, you need strong programming skills in Python, a solid understanding of machine learning algorithms, and a background in mathematics or statistics, often supported by a degree in computer science, engineering, or a related field. Familiarity with tools and libraries such as TensorFlow, scikit-learn, PyTorch, and version control systems like Git is essential, along with experience using data visualization and cloud platforms. Critical soft skills include problem-solving, adaptability, and effective communication to collaborate with cross-functional teams and explain complex models to stakeholders. These skills ensure the successful development, deployment, and maintenance of machine learning solutions that drive business value.

What is the difference between Python Ml Developer vs Data Scientist?

AspectPython Ml DeveloperData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; Python, ML certificationsBachelor's/Master's in Data Science, Statistics, or related; Python, ML certifications
Work EnvironmentSoftware development teams, AI/ML projectsResearch, data analysis, modeling teams
Employer & Industry UsageTech companies, startups, AI firmsFinance, healthcare, tech, research institutions
Common Search & ComparisonYesYes

Python ML Developers focus on building and deploying machine learning models using Python, often working closely with software engineering teams. Data Scientists analyze data, create models, and generate insights, often using Python along with statistical tools. While both roles require Python and ML knowledge, Python ML Developers are more involved in implementation and deployment, whereas Data Scientists focus on data analysis and research.

Can you do ML in Python?

Yes, Python is widely used for machine learning (ML) development due to its extensive libraries such as TensorFlow, scikit-learn, and PyTorch. Python skills are essential for a Python ML developer to build, train, and deploy ML models efficiently in various environments.
What are popular job titles related to Python Ml Developer jobs in Marietta, GA? For Python Ml Developer jobs in Marietta, GA, the most frequently searched job titles are:
What job categories do people searching Python Ml Developer jobs in Marietta, GA look for? The top searched job categories for Python Ml Developer jobs in Marietta, GA are:
What cities near Marietta, GA are hiring for Python Ml Developer jobs? Cities near Marietta, GA with the most Python Ml Developer job openings:
Python Ml Developer jobs near you
Infographic showing various Python Ml Developer job openings in Marietta, GA as of July 2026, with employment types broken down into 85% Full Time, 3% Part Time, 1% Temporary, and 11% Contract. Highlights an 82% Physical, 3% Hybrid, and 15% Remote job distribution, with an average salary of $115,579 per year, or $55.6 per hour.
Data Scientist with Python AI/ML

Data Scientist with Python AI/ML

Accord Technologies Inc.

Atlanta, GA • On-site

Contractor

Re-posted yesterday

Job description

Title : Data Scientist with Python AI/ML
Location: Atlanta, GA (Inperson interview needed)
Position type: W2 contract.
Job Description:

We are looking for a highly capable Technical Lead –Python & AI/ML with deep expertise in backend engineering, LLM-based applications, RAG architectures, and AI agent frameworks.
You will lead the design, development, and deployment of production-grade AI systems built on Python, modern LLM tooling, retrieval engines, embeddings, and vector databases.
This is a hands-on leadership role focused on building scalable and intelligent AI products.

Investment Banking and financial domain is needed.

Key Responsibilities

  • Lead the architecture and development of LLM-driven applications, AI agents, and RAG-based systems.
  • Provide technical guidance, conduct code reviews, and mentor junior team members.
  • Drive best practices in Python backend engineering, API development, and AI system design.

Backend Engineering (Python)

  • Build and maintain backend services using FastAPI or Flask.
  • Develop scalable API endpoints for AI applications, embeddings, and retrieval systems.
  • Ensure backend code quality, modularity, performance, and maintainability.

LLMs, RAG, and AI Agent Development

  • Build AI applications using: LangChain, LangGraph, Semantic Kernel, Haystack, LlamaIndex, AutoGen

•       Develop autonomous or semi-autonomous AI agents with tool calling and workflow graphs.

•       Implement Retrieval-Augmented Generation (RAG), embedding pipelines, chunking strategies, reranking, and grounding techniques.

•       Work with OpenAI SDK and other LLM providers (Anthropic, Azure OpenAI, Cohere, etc.).

•       Manage prompt engineering, prompt routing, safety guardrails, and evaluation metrics.

Data & Vector Search Engineering

•       Build data pipelines for indexing, embeddings, and retrieval workflows.

•       Work with SQL databases (PostgreSQL, MySQL, etc.) for metadata and application storage.

•       Work with vector databases such as: Redis, Postgres with pgvector, Elasticsearch, Neo4j, or others.

•       Implement and optimize search workflows using FAISS or similar similarity search libraries.

MLOps, Deployment & Observability

•       Deploy AI services using Docker, container orchestration, and cloud environments.

•       Implement monitoring for AI behavior, performance, error rates, and retrieval accuracy.

•       Set up CI/CD pipelines for backend and AI components.

•       Optimize inference cost, latency, and reliability.

Cross-Functional Collaboration

•       Collaborate with product, data engineering, and business teams to understand requirements.

•       Translate business problems into scalable AI architectures and deliver practical solutions.

•       Communicate technical decisions, trade-offs, and progress to stakeholders.

Required Qualifications

•       Bachelor’s/Master’s degree in Computer Science, AI/ML, Data Science, or related fields.

•       10+ years of experience in Python backend development.

•       Strong proficiency in FastAPI or Flask.

•       Strong working knowledge of SQL databases (Postgres, MySQL, etc.).

•  Hands-on expertise with vector databases:
Redis, Postgres/pgvector, Elasticsearch, or Neo4j.

•       Practical experience with FAISS for similarity search.

•       Hands-on experience with modern LLM frameworks:
LangChain, LangGraph, Semantic Kernel, Haystack, LlamaIndex, AutoGen.

•       Strong understanding of:

  • Embeddings & vector search
  • RAG pipelines
  • Retrieval optimization
  • Chunking strategies
  • Document loaders & indexing

•       Experience building AI apps using OpenAI SDK or similar.

•       Experience deploying APIs/services using Docker and cloud environments.

•       Leadership experience: guiding teams, conducting reviews, driving architecture decisions.