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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Engineer III 4P/791 - **Company:** 4P Consulting Inc. - **Location:** Atlanta, GA, United States - **Contract:** Temporary contract - **Skills:** Application Programming Interfaces (APIs), Artificial Intelligence, Microsoft Azure, Cloud Engineering, Continuous Integration, Information Engineering, Decision Support Systems, DevOps, Monitoring of Systems, Python (Programming Language), Machine Learning, Natural Language Processing, Azure Machine Learning, Search Technologies, Software Engineering, Unstructured Data, Google Cloud, Cloud Platform System, Feature Engineering, Data Ingestion, Pytorch, Retrieval-Augmented Generation, Large Language Models, Multi-Agent Systems, Model Validation, Build Management, AI Platforms, Kubernetes, HuggingFace, Machine Learning Operations, Databricks - **Published:** August 4, 2026 - **Apply:** https://www.indeed.com/viewjob?jk=2ebfc7102d473268 ## About the Role · Strong experience developing and deploying production-grade AI and machine learning solutions. · Hands-on experience with RAG architectures, LLM applications, multi-agent systems, and NLP. · Experience with Azure AI services, Google Cloud Platform AI services, or Azure Machine Learning. · Proficiency with Python and frameworks such as PyTorch, Transformers, or LangChain. · Experience deploying scalable models and AI services in cloud environments. · Knowledge of APIs, software engineering practices, model monitoring, and MLOps. · Experience working with structured and unstructured datasets. · Strong communication, collaboration, analytical, and problem-solving skills. Preferred Qualifications · Experience with Databricks, vector databases, embeddings, and semantic search. · Experience building reusable enterprise AI platforms or shared AI services. · Knowledge of model evaluation, data drift, observability, and responsible AI. · Familiarity with CI/CD, containers, Kubernetes, and cloud-native deployment. · Utility, energy, or regulated-industry experience is preferred. ## Description This role will focus on Retrieval-Augmented Generation, multi-agent systems, natural language processing, model deployment, and cloud-based AI solutions. The ideal candidate will have strong software engineering skills, hands-on AI/ML experience, and expertise with Azure or Google Cloud Platform., · Design and build modular, reusable AI components and services. · Develop scalable RAG solutions using structured and unstructured data. · Engineer multi-agent systems for task coordination, workflow automation, and decision support. · Build transcription and NLP pipelines for customer-interaction analysis. · Develop and fine-tune models using PyTorch, Hugging Face Transformers, LangChain, or similar frameworks. · Package and deploy models using Azure Machine Learning, Google Cloud Platform, or Databricks. · Integrate Databricks for data ingestion, feature engineering, experimentation, and model development. · Develop reusable libraries, APIs, templates, and engineering patterns. · Partner with MLOps, DevOps, data engineering, architecture, and product teams. · Implement monitoring for model performance, data drift, system usage, and operational reliability. · Ensure AI solutions meet enterprise security, privacy, compliance, scalability, and observability requirements. · Provide technical guidance to teams adopting shared AI products and components. ## Related Videos - [Introduction to Azure Machine Learning](https://www.wearedevelopers.com/videos/368-introduction-to-azure-machine-learning) - [From DevOps to Scaled DevOps: How We’re Rebuilding Continuous Delivery as a Platform](https://www.wearedevelopers.com/videos/100018-from-devops-to-scaled-devops-how-we-re-rebuilding-continuous-delivery-as-a-platform) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Cutting LLM Costs Without Cutting Quality: How to Beat Proprietary LLMs with Fine-Tuned Open Source](https://www.wearedevelopers.com/videos/100151-cutting-llm-costs-without-cutting-quality-how-to-beat-proprietary-llms-with-fine-tuned-open-source) - [Coffee with Developers - Maria Apazoglou](https://www.wearedevelopers.com/videos/1209-coffee-with-developers-maria-apazoglou) - [DevOps Maturity Check – a way to balance autonomy and alignment](https://www.wearedevelopers.com/videos/58-devops-maturity-check-a-way-to-balance-autonomy-and-alignment) ## Related Articles - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [Got AI ideas but no money? Here are 10 free ways to level up your AI skills with Google Cloud](https://www.wearedevelopers.com/magazine/600-got-ai-ideas-but-no-money-here-are-10-free-ways-to-level-up-your-ai-skills-with-google-cloud) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production)